Metrika članka

  • citati u SCindeksu: 0
  • citati u CrossRef-u:0
  • citati u Google Scholaru:[=>]
  • posete u poslednjih 30 dana:5
  • preuzimanja u poslednjih 30 dana:3
članak: 8 od 67  
Back povratak na rezultate
Anali Ekonomskog fakulteta u Subotici
2018, br. 39, str. 291-303
jezik rada: srpski
vrsta rada: stručni članak
doi:10.5937/AnEkSub1839291B


Primena inteligentnih tehnologija u visokom obrazovanju
aUniverzitet u Novom Sadu, Ekonomski fakultet, Subotica
bVisoka tehnička škola strukovnih studija, Novi Sad

e-adresa: bzita@ef.uns.ac.rs, oliverag@ef.uns.ac.rs, majadimi@gmail.com

Sažetak

Dostignuća veštačke inteligencija su posredstvom informacionih tehnologija inkorporirana u različite sfere savremenog života, pa ipak se u domenu visokog obrazovanja koriste tek sporadično. Upravo iz tog razloga u radu se analizirajuaktuelnidiversifikovani aspekti njihove primene u visokom obrazovanju. Prvi se tiče uključivanja ovih tehnologija u sam edukativni proces i obuhvata ekspertne i tutorske sisteme koji se, samostalno ili u kombinaciji s klasičnim metodološkim pristupima, koriste za obučavanje kako studenata, tako i nastavnog osoblja. Drugi aspekt su savetodavni sistemi, koji na automatizovan način pružaju podršku karijernom vođenju i usmeravanju studenata. Treći aspekt obuhvata otkrivanje znanja u podacima, s posebnim osvrtom na analizu nestrukturiranih podataka kakvi su sadržaji s društvenih medija relevantni za poslovanje i imidž visokoškolskih institucija ili pak veb logovi posetilaca institucionalnog veb-sajta. Prikazani pristupi i pozitivni primeri ilustruju komparativne prednosti inteligentnih tehnologija u domenu visokog obrazovanja i ukazuju na velike potencijalenjihove primene.

Ključne reči

veštačka inteligencija; inteligentne tehnologije; ekspertni sistemi; tutorski sistemi; rudarenje podataka; analiza sentimenta; analiza veb logova; visoko obrazovanje

Reference

Akerkar, R., Sajja, P. (2010) Knowledge-based systems. Jones & Bartlett Learning
Altrabsheh, N., Gaber, M.M., Coceaand, M.S.A.E. (2013) Sentiment analysis for education. u: 5th KES International Conference on Intelligent Decision Technologies, Proceedings, Vol. 255
Altrabsheh, N., Cocea, M., Fallahkhair, S. (2014) Learning Sentiment from Students’ Feedback for Real-Time Interventions in Classrooms. Cham: Springer Nature, str. 40-49
Al-Twijri, M.I., Noaman, A.Y. (2015) A New Data Mining Model Adopted for Higher Institutions. Procedia Computer Science, 65: 836-844
Anand, S.S., Mulvenna, M., Chevalier, K. (2003) On the deployment of web usage mining. u: EWMF 2003, Web Mining: from Web to Semantic Web, Cavtat-Dubrovnik, selected revised papers
Anjewierden, A.A., Kolloffel, B.J., Hulshof, C.D. (2007) Towards educational data mining: Using data mining methods for automated chat analysis to understand and support inquiry learning processes. u: International Workshop on Applying Data Mining in e-Learning, Crete, Greece
Badr, G., Algobail, A., Almutairi, H., Almutery, M. (2016) Predicting Students’ Performance in University Courses: A Case Study and Tool in KSU Mathematics Department. Procedia Computer Science, 82: 80-89
Berendt, B., Hollink, L., Hollink, V., Luczak-Rösch, M., Möller, K., Vallet, D. (2011) Usage analysis and the web of data. ACM SIGIR Forum, 45(1): 63
Bing, L. (2012) Sentiment analysis and opinion mining. Morgan & Claypool Publishers
Bonchi, F., Giannotti, F., Mazzanti, A., Pedreschi, D. (2003) ExAnte: Anticipated Data Reduction in Constrained Pattern Mining. Berlin, Heidelberg: Springer Nature, str. 59-70
de Oliveira, N.J.D., Nascimento, E.V. (2012) Intelligent Tutoring System for Distance Education. Journal of Information Systems and Technology Management, 9(1): 109-122
Facca, F.M., Lanzi, P.L. (2005) Mining interesting knowledge from weblogs: a survey. Data & Knowledge Engineering, 53(3): 225-241
Goodarzi, M.H., Rafe, V. (2012) Educational Advisor System Implemented by Web-Based Fuzzy Expert Systems. Journal of Software Engineering and Applications, 05(07): 500-507
Grljević, O. (2016) Sentiment u sadržajima društvenih medija kao instrument unapređenja poslovanja visokoškolskih institucija. Subotica: Ekonomski fakultet, doktorska disertacija
Hongjie, S. (2010) Research on student learning result system based on data mining. International Journal of Computer Science and Network Security, Vol. 10, No. 4: 203-205
Khanna, S., Kaushik, A., Barnela, M. (2010) Expert systems advances in education. u: National Conference on Computational Instrumentation, Chandigarh, India: CSIO, 109-112
Kurshan, B. (2016) The future of artificial intelligence in education. https//www.forbes.com/sites/barbarakurshan/2016/03/10/the-future-of-artificial-intelligence-in-education/#b103ba52e4d8
Litman, D.J., Forbes-Riley, K. (2004) Annotating student emotional states in spoken tutoring dialogues. u: 5th SIGdial Workshop on Discourse and Dialogue, 144-153; http://www.aclweb.org/anthology/W04-2326
Ma, W., Adesope, O.O., Nesbit, J.C., Liu, Q. (2014) Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 106(4): 901-918
Moursund, D. (2006) Brief introduction to educational implications of artificial intelligence. http://pages.uoregon.edu/moursund/Books/AIBook/AI.pdf
Nielsen, R.D., i dr. (2008) Annotating students' understanding of science concepts. u: Sixth International Conference on Language Resources and Evaluation, Marrakech, Proceedings, European Language Resources Association, http://people.cs.pitt.edu/~litman/courses/slate/pdf/873_paper.pdf.2-9517408-4-0
Peña-Ayala, A. (2014) Educational data mining: A survey and a data mining-based analysis of recent works. Expert Systems with Applications, 41(4): 1432-1462
Rashan, K.H., Peiris, A. (2011) Data mining applications in the education sector. MSIT, Carnegie Mellon University
Recker, M., Krumm, A., Feng, M., Grover, S., Koedinger, K. (2017) Educational data mining and learning analytics. https://circl.sri.com/archive/primers/CIRCL-Primer-LearningAnalytics.pdf
Romero, C., Ventura, S., Garcia, E. (2008) Data mining in course management system: Moodle case study and tutorial. An International Journal of Computers & Education, 51, str. 368-384
Sora, J.C., Sora, S.A. (2012) Artificial education: Expert systems used to assist and support 21stcentury education. GSTF Journal on Computing, Vol. 2, No. 3: 1-4
Tissera, W.M.R., Athauda, R.I., Fernando, H.C. (2011) Discovery of strongly related subjects in the undergraduate syllabi using data mining. u: IEEE International Conference on Information Acquisition, (57-62)
Vlahos, G.E., Ferratt, T.W., Knoepfle, G. (2004) The use of computer-based information systems by German managers to support decision making. Information & Management, 41(6): 763-779
Wang, J., Lo, E., Yiu, M.L., Tong, J., Wang, G., Liu, X. (2013) The impact of solid state drive on search engine cache management. u: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13, New York: Association for Computing Machinery (ACM), str. 693
Yong, W.L., Zhang, Z.Y. (2005) Mining sequential association - rule for improving web document prediction. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, Vol. 37, No. 6
Zaiane, O.R., Srivastava, J., Spiliopoulou, M., Masand, B., ur. (2002) Mining web data for discovering usage patterns and profiles. u: 4th International Workshop, July 23, Edmonton, Canada
Zailani, A., Herawan, T., Deris, M.M. (2013) Discovering interesting association rules from student admission data set. Lecture Notes in Electrical Engineering, Vol. 285, 135-142