Process Mining Methodology for Digital Processes under Smart Campus Concept

Yıl 2022, , 1006 - 1018, 31.12.2022

Onur Doğan , Esra Cengiz Tırpan

https://doi.org/10.35193/bseufbd.1162284

Öz

Digital transformation affects universities as well as many industries. Universities are increasingly using various digital resources and systems to manage their knowledge. The smart campus, on the other hand, supports informed decision-making by integrating these resources and systems. Process mining provides real insights for digital transformation, allowing processes to be examined more transparently. This study aims to examine the proposed project implementation processes related to the smart university with the process mining methodology. For this purpose, 32 completed projects submitted to İzmir Bakırçay University Scientific Research Projects Coordinatorship (BAPK) with the proposed methodology adapted from Deming's continuous improvement cycle were examined. The data are taken from two different pages in the project automation system. According to the research findings, Projects are grouped into three categories: Guided Projects (GDM, 5 projects), Graduate Thesis Projects (TEZ, 5 projects), and Career Start Support Projects (KBP, 22 projects). 40.6% (13 projects) of the applications went directly to the project review stage, while 19 (59.4%) needed procedural correction. Considering the time from the creation of the application of 32 projects to the signing of the contract, it is seen that the arithmetic average of the cycle time is 15.1 weeks, and the median average is 52.5 days. The notable difference between arithmetic and median mean is that very few projects are of long duration. Procedural adjustments affect project evaluation cycle time by an additional 14 days. The carelessness or lack of knowledge of the applicants extends the cycle time of the process from 15 days to 53 days. The total duration of unnecessary waiting time in the process is 17 days. This study primarily proposes that non-digital processes should be digitized as soon as possible.

Anahtar Kelimeler

Process Mining, Smart Campus, Digital Transformation, Process Management

Akıllı Kampüs Konsepti Altında Dijital Süreçler İçin Süreç Madenciliği Metodolojisi

Öz

Dijital dönüşüm, birçok endüstriyi etkilediği gibi üniversiteleri de etkilemektedir. Üniversiteler, sahip olduğu bilgiyi yönetmek için, çeşitli dijital kaynaklardan ve sistemlerden giderek daha fazla faydalanmaktadır. Akıllı kampus ise, bu kaynakları ve sistemleri entegre ederek, bilinçli karar verme sürecine destek olur. Süreç madenciliği, süreçlerin daha şeffaf incelenmesine olanak tanıyarak, dijital dönüşüm için gerçek öngörüler sunar. Bu çalışma, akıllı üniversite ile ilgili önerilen proje uygulama süreçlerini, süreç madenciliği metodolojisi ile incelemeyi amaçlamaktadır. Bu amaç doğrultusunda, Deming'in sürekli iyileştirme döngüsünden uyarlanan önerilen metodoloji ile İzmir Bakırçay Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü (BAPK)’ye sunulan ve tamamlanmış 32 proje incelenmiştir. Veriler proje otomasyon sisteminde yer alan iki farklı sayfadan alınmıştır. Araştırma bulgularına göre; Projeler, Rehberli Proje (GDM, 5 proje), Lisansüstü Tez Projeleri (TEZ, 5 proje) ve Kariyer Başlangıç Destek Projeleri (KBP, 22 proje) olmak üzere üç kategoride gruplandırılmıştır. 32 projenin başvurusunun oluşturulmasından sözleşmenin imzalanmasına kadar geçen süreye bakıldığında çevrim süresinin aritmetik ortalamasının 15,1 hafta, medyan ortalamasının ise 52,5 gün olduğu görülmektedir. Aritmetik ve medyan ortalama arasındaki dikkate değer fark, çok az projenin uzun süreli olmasından kaynaklanmaktadır. Prosedürel düzeltmeler proje değerlendirmesinin döngü süresini fazladan 14 gün etkilemektedir. Başvuru sahiplerinin dikkatsizliği veya bilgi eksikliği, sürecin döngü süresini 15 günden 53 güne kadar uzatmaktadır. Süreçteki gereksiz bekleme süresinin toplam süresi 17 gündür. Bu çalışma öncelikle, dijital olmayan süreçlerin mümkün olan en kısa sürede dijitalleştirilmesi gerektiğini önermektedir. Başvuruların %40,6'sı (13 proje) doğrudan proje inceleme aşamasına geçerken, 19'u (%59,4) prosedürel düzeltmeye ihtiyaç duymuştur.

Anahtar Kelimeler

Süreç Madenciliği, Akıllı Kampüs, Dijital Dönüşüm, Süreç Yönetimi

Kaynakça

• Ahmed, V., Abu Alnaaj, K., &Saboor, S. (2020). An investigation into stakeholders’ perception of smart campus criteria: the American university of Sharjah as a case study. Sustainability, 12(12), 1-24.
• Barba-Sánchez, V., Arias-Antúnez, E., & Orozco-Barbosa, L. (2019). Smart cities as a source for entrepreneurial opportunities: Evidence for Spain. Technological Forecasting and Social Change, 148(2019), 1-10.
• Kondepudi, S. N., Ramanarayanan, V., Jain, A., Singh, G. N., Nitin Agarwal, N. K., Kumar, R., ... & Gemma, P. (2014). Smart sustainable cities analysis of definitions. The ITU-T focus group for smart sustainable cities.
• Richter, C., Kraus, S., & Syrjä, P. (2015). The Smart City as an opportunity for entrepreneurship. International Journal of Entrepreneurial Venturing, 7(3), 211-226.
• Giffinger, R., Fertner, C., Kramar, H., &Meijers, E. (2007). City-ranking of European medium-sized cities. Cent. Reg. Sci. Vienna UT, 9(1), 1-12.
• Hollands, R. G. (2020). Will The Real Smart City Please Stand Up? Intelligent, Progressive or Entrepreneurial? The Routledge Companion to Smart Cities 1st ed. Routledge, 179-199.
• Bakıcı, T., Almirall, E., & Wareham, J. (2013). A smart city initiative: the case of Barcelona. Journal Of the Knowledge Economy, 4(2), 135-148.
• Huang, L. S., Su, J. Y., & Pao, T. L. (2019). A context aware smart classroom architecture for smart campuses. Applied Sciences, 9(9), 1837.
• Aldowah, H., Rehman, S. U., Ghazal, S., & Umar, I. N. (2017). Internet Of Things in Higher Education: A Study on Future Learning. The 6th International Conference on Computer Science and Computational Mathematics (ICCSCM 2017). 4–5 May 2017, Malaysia, 1-10.
• Muhamad, W., Kurniawan, N. B., & Yazid, S. (2017). Smart Campus Features, Technologies, And Applications: A Systematic Literature Review. International Conference on Information Technology Systems and Innovation (ICITSI).23-24 October, Bandung,384-391.
• Pagliaro, F., Mattoni, B., Gugliermenti, F., Bisegna, F., Azzaro, B., Tomei, F., &Catucci, S. (2016, June). A Roadmap Toward the Development of Sapienza Smart Campus. In 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 7-10 June, Florence,1-6.
• Huang, C. (2017, December). On Study of Building Smart Campus under Conditions of Cloud Computing And Internet of Things. 1st International Global on Renewable Energy and Development (IGRED 2017), 22–25 December, Singapore, 1-6.
• Lane, J. E., &Finsel, B. A. (2014). Fostering Smarter Colleges and Universities. Building A Smarter University: Big Data, Innovation, and Analytics, Sunny Press, New York 3-26.
• Tan, H., Chen, S., Shi, Q., & Wang, L. (2014). Development of green campus in China. Journal of Cleaner Production, 64, 646-653.
• Ng, J. W., Azarmi, N., Leida, M., Saffre, F., Afzal, A., &Yoo, P. D. (2010). The Intelligent Campus (Icampus): End-To-End Learning Lifecycle of a Knowledge Ecosystem. Sixth International Conference on Intelligent Environments,19-21 July 2010, Malaysia, 332-337.
• Hirsch, B., & Ng, J. W. (2011). Education Beyond the Cloud: Anytime-Anywhere Learning in A Smart Campus Environment. International Conference for Internet Technology and Secured Transactions,11-14 December, Abu Dhabi, 718-723.
• Fantinato, M., Gimenes, I. M. D. S., & de Toledo, M. B. F. (2009). Product Line in The Business Process Management Domain. In Applied Software Product Line Engineering, Auerbach Publications, New York, 519-552.
• Reinkemeyer, L. (2020). Business View: Towards A Digital Enabled Organization. In Process Mining in Action, Springer, Cham, 197-206.
• Dogan, O. (2020). Discovering customer paths from location data with process mining. European Journal of Engineering Science and Technology, 3(1), 139-145.
• Lillig, G. (2020). Telekom: Process Mining in Shared Services. In Process Mining in Action, Springer, Cham, 169-178.
• Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., &Veit, F. (2018). Process Mining and Robotic Process Automation: A Perfect Match. 16th International Conference on Business Process Management, 9-14 September, Sydney, 124-131.
• Dogan, O., &Öztaysi, B. (2018). In-store behavioral analytics technology selection using fuzzy decision making. Journal of Enterprise Information Management, 31, 612–630.
• Grisold, T., Mendling, J., Otto, M., &vomBrocke, J. (2020). Adoption, use and management of process mining in practice. Business Process Management Journal, 27(2), 369-387.
• Aguirre, S., Parra, C., & Sepúlveda, M. (2017). Methodological proposal for process mining projects. International Journal of Business Process Integration and Management, 8(2), 102-113.
• Van Der Aalst, W. M., Reijers, H. A., Weijters, A. J., van Dongen, B. F., De Medeiros, A. A., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732.
• Dogan, O., & Gurcan, O. F. (2022). Applications Of Big Data and Green Iot-Enabling Technologies For Smart Cities. In Research Anthology on Big Data Analytics, Architectures, And Applications, IGI Global, 1090-1109.
• Coccoli, M., Guercio, A., Maresca, P., &Stanganelli, L. (2014). Smarter universities: A vision for the fast-changing digital era. Journal of Visual Languages & Computing, 25(6), 1003-1011.
• Liu, M., & Li, L. (2018). The Construction of Smart Campus In Universities And The Practical Innovation Of Student Work. 2018 International Conference on Information Management & Management Science (IMMS2018), 25-27 August, China, 154-157.
• Lin, Y. B., Chen, L. K., Shieh, M. Z., Lin, Y. W., & Yen, T. H. (2018). CampusTalk: IoT devices and their interesting features on campus applications. IEEE Access, 6, 26036-26046.
• Alvarez-Campana, M., López, G., Vázquez, E., Villagrá, V. A., &Berrocal, J. (2017). Smart CEI moncloa: An iot-based platform for people flow and environmental monitoring on a Smart University Campus. Sensors, 17(12), 2856.
• Chieochan, O., Saokaew, A., &Boonchieng, E. (2017). IOT For Smart Farm: A Case Study of The Lingzhi Mushroom Farm atMaejo University. 14th International Joint Conference on Computer Science and Software Engineering (JCSSE),12-14 July, Thailand, 1-6.
• Jain, M., Kaushik, N., &Jayavel, K. (2017). Building Automation and Energy Control Using Iot-Smart Campus.2nd International Conference on Computing and Communications Technologies (ICCCT), 23-24 February, India, 353-359.
• Xiao, J. (2019). Digital transformation in higher education: critiquing the five-year development plans (2016-2020) of 75 Chinese universities. Distance Education, 40(4), 515-533.
• Flavin, M. (2016). Disruptive conduct: the impact of disruptive technologies on social relations in higher education. Innovations in Education and Teaching International, 53(1), 3-15.
• T. Shakib (2006). Cisco Digital Ceiling: Enhanced Learning Through Technology and Digitization.https://blogs.cisco.com/digital/cisco-digital-ceiling-enhanced-learning-through-technology-and-digitization, (28 July 2022).
• Romero, C., Cerezo, R., Bogarín, A., & Sánchez‐Santillán, M. (2016). Educational Process Mining: A Tutorial and Case Study Using Moodle Data Sets. Data Mining and Learning Analytics: Applications In Educational Research, Wiley, 1-28.
• A. Sypsas& K. Dimitris (2022). Reviewing process mining applications and techniques in education, International Journal of Artificial Intelligence and Applications 13(2022) 83–102.
• Trcka, N., &Pechenizkiy, M. (2009). From Local Patterns to Global Models: Towards Domain Driven Educational Process Mining. Ninth international conference on intelligent systems design and applications, 30 November- 02 December, Pisa, 1114-1119.
• Bogarín, A., Romero, C., Cerezo, R., & Sánchez-Santillán, M. (2014). Clustering For Improving Educational Process Mining. Fourth International Conference on Learning Analytics and Knowledge, 24-28 March, USA, 11-15.
• Ayutaya, N. S. N., Palungsuntikul, P., &Premchaiswadi, W. (2012). Heuristic Mining: Adaptive Process Simplification in Education. Tenth International Conference on ICT And Knowledge Engineering 21-23 November, Thailand, 221-227.
• Etinger, D., Orehovački, T., & Babić, S. (2018). Applying Process Mining Techniques to Learning Management Systems for Educational Process Model Discovery and Analysis. International Conference on Intelligent Human Systems Integration, Springer, Cham, 420-425.
• Etinger, D. (2020). Discovering And Mapping LMS Course Usage Patterns to Learning Outcomes. In International Conference on Intelligent Human Systems Integration, Springer, Cham, 486-491.
• Doleck, T., Basnet, R. B., Poitras, E. G., & Lajoie, S. P. (2015). Mining learner–system interaction data: implications for modeling learner behaviors and improving overlay models. Journal of Computers in Education, 2(4), 421-447.
• Deeva, G., &Weerdt, J. D. (2018). Understanding Automated Feedback in Learning Processes By Mining Local Patterns. In International Conference on Business Process Management, Springer, Cham, 56-68.
• Ramaswami, G., Susnjak, T., Mathrani, A., Lim, J., & Garcia, P. (2019). Using educational data mining techniques to increase the prediction accuracy of student academic performance. Information and Learning Sciences, 120(7/8), 451-467.
• Dolak, R. (2019). Using process mining techniques to discover student’s activities, navigation paths, and behavior in LMSMoodle. International Conference on Innovative Technologies and Learning (ICTL’19), 2-5 December, Norway, 129-138.
• Salazar-Fernandez, J. P., Sepúlveda, M., Munoz-Gama, J., & Nussbaum, M. (2021). Curricular analytics to characterize educational trajectories in high-failure rate courses that lead to late dropout. Applied Sciences, 11(4), 1436.
• Downes, S., & Campbell, C. (2018, March). Smart University Utilising the Concept of the Internet of Things (IOT). UKSim-AMSS 20th International Conference on Computer Modelling and Simulation (UKSim), 27-29 March, UK, 145-150.
• Bagdasarian, I. S., Stupina, A. A., Goryacheva, O. E., & Shmeleva, Z. N. (2020). The University Digital Transformation as A Tool for Human Capital Development.1st International Scientific Conference, 8-9 October, Russian Federation, 1-5.
• Pham, T. V., Nguyen, A. T. T., Ngo, T. D., Le, D. H., Le, K. C., Nguyen, T. H., & Le, H. Q. (2020). Proposed Smart University Model as A Sustainable Living Lab for University Digital Transformation. 5th International Conference on Green Technology and Sustainable Development (GTSD),27-28 November, Vietnam, 472-479. IEEE.
• Alexander, N., Olga, V., Anna, G., Yana, M., & Andrey, V. (2021). The managing the University Digital Transformation based on Big Data. International Conference on Information Technology and Nanotechnology (ITNT), 20-24 September, Russian Fedaration,1-5.
• Giang, N. T. H., Hai, P. T. T., Tu, N. T. T., & Tan, P. X. (2021). Exploring the readiness for digital transformation in a higher education institution towards industrial revolution 4.0. International Journal of Engineering Pedagogy, 11(2), 4-24.
• Han, K. H., Hwang, B., & Jeon, J. (2015). A navigation pattern analysis of university department’s websites using a processing mining approach. Innovations in Education and Teaching International, 52(5), 485-498.
• Cameranesi, M., Diamantini, C., Genga, L., &Potena, D. (2017). Students' Careers Analysis: A Process Mining Approach.7th International Conference on Web Intelligence, Mining and Semantics,19 – 22 June, Italy, 1-7.
• Uzir, N. A. A., Gašević, D., Jovanović, J., Matcha, W., Lim, L. A., & Fudge, A. (2020). Analytics of Time Management and Learning Strategies for Effective Online Learning in Blended Environments. Tenth International Conference on Learning Analytics & Knowledge, 23-27 March, Cyberspace,392-401.
• Davis, S. K., &Hadwin, A. F. (2021). Exploring differences in psychological well-being and self-regulated learning in university student success. Frontline Learning Research, 9(1), 30-43.
• Kostepen, Z. N., Akkol, E., Dogan, O., Bitim, S., & Hiziroglu, A. (2020). A Framework for Sustainable and Data-driven Smart Campus. 22nd International Conference on Enterprise Information Systems, 5-7 May, 746-753.
• Dogan, O., Bitim, S., & Hiziroglu, K. (2021). A v-model software development application for sustainable and smart campus analytics domain. Sakarya University Journal of Computer and Information Sciences, 4(1), 111-119.