Description:
[1] Abuzinadah, N., Umer, M., Ishaq, A., Hejaili, A.A., Alsubai, S., Eshmawi, A.A.,
Mohamed, A. and Ashraf, I., 2023. Role of convolutional features and machine
learning for predicting student academic performance from MOODLE data. PLoS
ONE. Public Library of Science, vol. 18. URL https://doi.org/10.1371/journal.pone.
0293061.
[2] Afini Normadhi, N.B., Shuib, L., Md Nasir, H.N., Bimba, A., Idris, N. and Balakrishnan, V., 2019. Identification of personal traits in adaptive learning environment:
Systematic literature review. Computers and Education, 130, pp.168–190. URL
https://doi.org/10.1016/j.compedu.2018.11.005.
[3] Aguar, K.E., 2018. Sail: a system for adaptive interest-based learning in stem education. PhD thesis. University of Georgia. URL http://hdl.handle.net/10724/37603.
[4] Ako-Nai, F., Tan, Q., Pivot, F.C. and Kinshuk, 2012. The 5R adaptive learning
content generation platform for mobile learning. Proceedings - 2012 IEEE 4th International Conference on Technology for Education, T4E 2012. pp.132–137. URL
https://doi.org/10.1109/T4E.2012.22.
[5] Albert, D. and Steiner, C.M., 2011. Reflections on the evaluation of adaptive learning technologies. Proceedings - IEEE International Conference on Technology for
Education, T4E 2011. pp.295–296. URL https://doi.org/10.1109/T4E.2011.62.
[6] Aleven, V., McLaughlin, E., Glenn, R.A. and Koedinger, K.R., 2016. Instruction
based on adaptive learning technologies. Handbook of Research on Learning and
Instruction, Second edition. Taylor and Francis, pp.522–559. URL https://doi.org/
10.4324/9781315736419-33.
[7] Aljojo, N., Adams, C., Saifuddin, H. and Alsehaimi, Z., 2011. Evaluating the impact of an Arabic version of an adaptive learning system based on the felder-silverman’s learning style instrument. In: A. Rospigliosi and S. Greener, eds. Proceedings of the European Conference on Games-based Learning. Dechema e.V., vol. 2,
pp.897–908. URL https://www.academia.edu/6160042.
[8] Allison, G.L. and Extavour, R.M., 2017. Pharmacy Students’ Perceptions and Usage
of an Adaptive Learning Technology (SmartBook®) in Anatomy and Physiology
in a Caribbean School of Pharmacy. Ubiquitous Learning, 10(3), pp.1–9. URL
https://doi.org/10.18848/1835-9795/CGP/v10i03/1-9.
[9] Ananta, I.G.P., 2004. Using an adaptive web-based learning environment to develop
conceptual and procedural knowledge. PhD thesis. University of Wollongong. URL
https://ro.uow.edu.au/theses/202.
[10] Anderman, E.M. and Midgley, C., 2014. Methods for Studying Goals, Goal Structures, and Patterns of Adaptive Learning. In: R.W. Roeser, R. Marachi and
H. Gehlbach, eds. Goals, Goal Structures, and Patterns of Adaptive Learning. Taylor
and Francis, pp.1–20. URL https://doi.org/10.4324/9781410602152-8.
[11] Andrukhiv, A.I., 2015. Methods and means of adaptive support of university learning
process with library materials. Thesis for a Ph.D degree in specialty 01.05.03 –
mathematical and software development for computer systems. Lviv Polytechnic
National University, Lviv. URL https://nrat.ukrintei.ua/searchdoc/0415U005842.
[12] Angelaccio, M. and Buttarazzi, B., 2011. EduSHARE®: A peer to peer document
sharing system for obtaining adaptive learning procedures. International Journal
of Technology Enhanced Learning, 3(5), pp.525–535. URL https://doi.org/10.1504/
IJTEL.2011.042103.
[13] Bai, P., Zhang, X., Dai, F., Wang, J. and Wang, X., 2018. Research on the Adaptive
Learning Support System of Air Traffic Control. In: X. Wang, Y. Zhang, D. Yang
and Z. You, eds. CICTP 2018: Intelligence, Connectivity, and Mobility - Proceedings of the 18th COTA International Conference of Transportation Professionals. American
Society of Civil Engineers (ASCE), pp.2234–2245. URL https://doi.org/10.1061/
9780784481523.222.
[14] Basitere, M. and Ivala, E., 2017. Evaluation of an adaptive learning technology
in a first-year extended curriculum programme physics course. South African
Computer Journal, 29(3), pp.1–15. URL https://doi.org/10.18489/sacj.v29i3.476.
[15] Bayounes, W., Saadi, I.B., Kinshuk and Gh ˆ ezala Ben, H., 2012. Towards a frame- ´
work definition for learning process engineering supported by an adaptive learning system. Proceedings - 2012 IEEE International Conference on Technology Enhanced Education, ICTEE 2012. p.6208662. URL https://doi.org/10.1109/ICTEE.2012.
6208662.
[16] Bian, C., Dong, S., Li, C., Shi, Z. and Lu, W., 2017. Generation of adaptive learning
path based on concept map and immune algorithm. ICCSE 2017 - 12th International
Conference on Computer Science and Education. Institute of Electrical and Electronics Engineers Inc., pp.409–414. URL https://doi.org/10.1109/ICCSE.2017.8085526.
[17] Bobrova, T.A., 2011. Theoretical and methodical means of adaptive management
socio-pedagogical subsystems of a higher educational institution. (0211U008967).
Kharkiv National University of Economics. URL https://nrat.ukrintei.ua/
searchdoc/0211U008967.
[18] Borsuk, S.P., 2011. Operators adaptive learning on the functional trainer. The thesis for maintaining the academic degree of candidate of engineering science on
speciality 05.07.14 – Air-space trainers. National aviation university, Kyiv. URL
https://nrat.ukrintei.ua/searchdoc/0411U007122.
[19] Bouzenada, S.N.E., Boissier, O. and Zarour, N.E., 2018. An agent-based approach for personalised and adaptive learning. International Journal of Technology Enhanced Learning, 10(3), pp.184–201. URL https://doi.org/10.1504/IJTEL.2018.
092701.
[20] Cabinet of Ministers of Ukraine, 2022. Stratehiia rozvytku vyshchoi osvity v
Ukraini na 2022-2032 roky [On approval of the Strategy of higher education development in Ukraine for 2022–2032]. URL https://zakon.rada.gov.ua/laws/show/
286-2022-%D1%80#Text.
[21] Centre for Science and Technology Studies, Leiden University, The Netherlands,
2022. Vosviewer - visualizing scientific landscapes. URL https://www.vosviewer.
com/.
[22] Chang, Y.H., Chen, Y.Y., Chen, N.S., Lu, Y.T. and Fang, R.J., 2016. Yet another
adaptive learning management system based on Felder and Silverman’S Learning Styles and Mashup. Eurasia Journal of Mathematics, Science and Technology
Education, 12(5), pp.1273–1285. URL https://doi.org/10.12973/eurasia.2016.1512a.
[23] Chaoui, M. and Laskri, M.T., 2013. Proposition and organization of an adaptive
learning domain based on fusion from the web. Educational Technology and Society, 16(1), pp.118–132. URL https://api.semanticscholar.org/CorpusID:241317.
[24] Chaplot, D.S., Rhim, E. and Kim, J., 2016. Personalized adaptive learning using
neural networks. L@S 2016 - Proceedings of the 3rd 2016 ACM Conference on
Learning at Scale. Association for Computing Machinery, Inc, pp.165–168. URL
https://doi.org/10.1145/2876034.2893397.
[25] Chauhan, J., Taneja, S. and Goel, A., 2016. Enhancing MOOC with Augmented
Reality, Adaptive Learning and Gamification. Proceedings of the 2015 IEEE 3rd
International Conference on MOOCs, Innovation and Technology in Education, MITE
2015. Institute of Electrical and Electronics Engineers Inc., pp.348–353. URL https:
//doi.org/10.1109/MITE.2015.7375343.
[26] Cho, K., Raiko, T. and Ilin, A., 2011. Enhanced gradient and adaptive learning
rate for training restricted Boltzmann machines. Proceedings of the 28th International Conference on Machine Learning, ICML 2011. pp.105–112. URL https:
//www.academia.edu/14198472.
[27] Chou, C.Y., Lai, K., Chao, P.Y., Lan, C.H. and Chen, T.H., 2015. Negotiation based
adaptive learning sequences: Combining adaptivity and adaptability. Computers and Education, 88, pp.215–226. URL https://doi.org/10.1016/j.compedu.2015.
05.007.
[28] Chou, C.Y., Lai, K.R., Chao, P.Y., Tseng, S.F. and Liao, T.Y., 2018. A negotiationbased adaptive learning system for regulating help-seeking behaviors. Computers
and Education, 126, pp.115–128. URL https://doi.org/10.1016/j.compedu.2018.07.
010.
[29] Chuvasov, M., 2020. Forming the readiness of future teachers to use information
and cognitive technologies as a factor of their professionalism and skills development. Bulletin of the Cherkasy Bohdan Khmelnytsky National University. Series “Pedagogical Sciences”, (3), pp.164–168. URL https://ped-ejournal.cdu.edu.ua/
article/view/3939.
[30] Clougherty, R.J. and Popova, V., 2015. How adaptive is adaptive learning: Seven
models of adaptivity or finding Cinderella’s shoe size. International Journal of Assessment and Evaluation, 22(2), pp.13–22. URL https://doi.org/10.18848/2327-7920/
CGP/v22i02/48369.
[31] Cohen, J., 1988. 2nd ed. New York: Routledge. URL https://doi.org/10.4324/
9780203771587.
[32] Covington, M.V., 2014. Patterns of Adaptive Learning Study: Where Do We Go
From Here? In: C. Midgley, ed. Goals, Goal Structures, and Patterns of Adaptive Learning. Taylor and Francis, pp.279–294. URL https://doi.org/10.4324/
9781410602152-17.
[33] Cui, W., Xue, Z., Shen, J., Sun, G. and Li, J., 2019. The Item Response Theory Model
for an AI-based Adaptive Learning System. 2019 18th International Conference on
Information Technology Based Higher Education and Training, ITHET 2019. Institute
of Electrical and Electronics Engineers Inc., p.8937383. URL https://doi.org/10.
1109/ITHET46829.2019.8937383.
[34] Daniel, J., Cano, E.V. and Gisbert Cervera, M., 2015. The future of MOOCs: Adaptive learning or business model? [El futuro de los MOOC: ¿Aprendizaje adaptado
o modelo de negocio?]. RUSC Universities and Knowledge Society Journal, 12(1),
pp.64–73. URL https://doi.org/10.7238/rusc.v12i1.2475.
[35] Daniello, G., Granito, A., Mangione, G., Miranda, S., Orciuoli, F., Ritrovato, P.
and Rossi, P.G., 2014. A city-scale situation-aware adaptive learning system. In:
D.G. Sampson, M.J. Spector, N.S. Chen, R. Huang and Kinshuk, eds. Proceedings
- IEEE 14th International Conference on Advanced Learning Technologies, ICALT
2014. Institute of Electrical and Electronics Engineers Inc., pp.136–137. URL https:
//doi.org/10.1109/ICALT.2014.47.
[36] Davis, P., Long, P., Adams, D., Corliss, S., Liu, M., McKelroy, E., Tothero, K.,
Walker, J. and Ziai, K., 2016. Use of adaptive learning to prepare first-year pharmacy students: Our experience. In: J.M. Spector, C.C. Tsai, R. Huang, P. Resta, D.G.
Sampson, Kinshuk and N.S. Chen, eds. Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016. Institute of Electrical and
Electronics Engineers Inc., pp.72–74. URL https://doi.org/10.1109/ICALT.2016.139.
[37] De-La-Fuente-Valent´ın, L., Pardo, A. and Kloos, C.D., 2011. Generic service integration in adaptive learning experiences using IMS learning design. Computers and Education, 57(1), pp.1160–1170. URL https://doi.org/10.1016/j.compedu.2010.
12.007.
[38] De Marsico, M., Sterbini, A. and Temperini, M., 2011. The definition of a tunneling strategy between adaptive learning and reputation-based group activities. Proceedings of the 2011 11th IEEE International Conference on Advanced Learning Technologies, ICALT 2011. pp.498–500. URL https://doi.org/10.1109/ICALT.2011.155.
[39] De Santana, S.J., Paiva, R., Bittencourt, I.I., Ospina, P.E., De Amorim Silva, R. and
Isotani, S., 2016. Evaluating the impact of mars and venus effect on the use of an
adaptive learning technology for Portuguese and mathematics. In: J.M. Spector,
C.C. Tsai, R. Huang, P. Resta, D.G. Sampson, Kinshuk and N.S. Chen, eds. Proceedings - IEEE 16th International Conference on Advanced Learning Technologies,
ICALT 2016. Institute of Electrical and Electronics Engineers Inc., pp.31–35. URL
https://doi.org/10.1109/ICALT.2016.58.
[40] Del Blanco, A., Torrente, J., Moreno-Ger, P. and Fernandez-Manj ´ on, B., 2013. En- ´
hancing adaptive learning and assessment in virtual learning environments with
educational games. In: Information Resources Management Association, ed. K12 Education: Concepts, Methodologies, Tools, and Applications. Hershey, PA: IGI
Global, vol. 2, pp.578–597. URL https://doi.org/10.4018/978-1-4666-4502-8.ch034.
[41] Di Mascio, T., Vittorini, P., Gennari, R., Melonio, A., De La Prieta, F. and Alrifai,
M., 2012. The learners’ user classes in the TERENCE adaptive learning system.
Proceedings of the 12th IEEE International Conference on Advanced Learning Technologies, ICALT 2012. pp.572–576. URL https://doi.org/10.1109/ICALT.2012.68.
[42] Digital Education Action Plan (2021–2027), 2020. URL https://education.ec.europa.
eu/focus-topics/digital-education/digital-education-action-plan.
[43] Dong, C. and Sharma, N., 2015. Flipping the classroom with adaptive learning technology. Medical Teacher, 37(10), p.976. URL https://doi.org/10.3109/0142159X.
2015.1045846.
[44] Durieu, J., Solal, P. and Tercieux, O., 2011. Adaptive learning and p-best response
sets. International Journal of Game Theory, 40(4), pp.735–747. URL https://doi.org/
10.1007/s00182-010-0266-2.
[45] Dziuban, C., Moskal, P., Parker, L., Campbell, M., Howlin, C. and Johnson, C.,
2018. Adaptive learning: A stabilizing influence across disciplines and universities.
Online Learning Journal, 22(3), pp.7–39. URL https://doi.org/10.24059/olj.v22i3.
1465.
[46] Dziuban, C.D., Moskal, P.D., Cassisi, J. and Fawcett, A., 2016. Adaptive learning in
psychology: Wayfinding in the digital age. Online Learning Journal, 20(3), pp.74–
96. URL https://doi.org/10.24059/olj.v20i3.972.
[47] Elbrekht, O.M., 2004. Adaptable Management of Educational Process in Secondary
Comprehensive School with Humanitarian Slant. Thesis for Candidate’s Degree in
Pedagogics by speciality 13.00.01 - Theory and History of Pedagogics. Central
Institute of Postgraduate Educational Studies of APS of Ukraine, Kyiv. URL https:
//nrat.ukrintei.ua/searchdoc/0404U001835.
[48] Essa, A., 2016. A possible future for next generation adaptive learning systems. Smart Learning Environments, 3(1), p.16. URL https://doi.org/10.1186/
s40561-016-0038-y.
[49] 2014. Evaluating adaptive learning model. Proceedings of 2014 International Conference on Interactive Collaborative Learning, ICL 2014. Institute of Electrical and Electronics Engineers Inc., pp.818–822. URL https://doi.org/10.1109/ICL.2014.7017878.
[50] Extavour, R.M., Ocho, O. and Allison, G.L., 2019. Nursing students’ attitudes
toward an adaptive learning technology in a pharmacology course. Ubiquitous Learning, 12(4), pp.25–35. URL https://doi.org/10.18848/1835-9795/CGP/v12i04/
25-35.
[51] Fadieieva, L. and Semerikov, S., 2024. ADANCO output on dataset from
https://zenodo.org/doi/10.5281/zenodo.10938018. URL https://ssemerikov.github.
io/Fadieieva/.
[52] Fadieieva, L. and Semerikov, S., 2024. KSPU Moodle activities and marks 2020-
2022. URL https://doi.org/10.5281/zenodo.10938019.
[53] Fadieieva, L.O., 2021. Enhancing adaptive learning with Moodle’s machine learning. Educational Dimension, 5, p.1–7. URL https://doi.org/10.31812/ed.625.
[54] Fadieieva, L.O., 2023. Adaptive learning: a cluster-based literature review (2011-
2022). Educational Technology Quarterly, 2023(3), p.319–366. URL https://doi.org/
10.55056/etq.613.
[55] Fadieieva, L.O., 2023. Adaptive learning concept selection: a bibliometric review
of scholarly literature from 2011 to 2019. Educational Dimension, 9, p.136–148.
URL https://doi.org/10.31812/ed.643.
[56] Fadieieva, L.O., 2023. Bibliometric Analysis of Adaptive Learning Literature from
2011-2019: Identifying Primary Concepts and Keyword Clusters. In: G. Antoniou,
V. Ermolayev, V. Kobets, V. Liubchenko, H.C. Mayr, A. Spivakovsky, V. Yakovyna
and G. Zholtkevych, eds. Information and Communication Technologies in Education, Research, and Industrial Applications. Cham: Springer Nature Switzerland, Communications in Computer and Information Science, pp.215–226. URL
https://doi.org/10.1007/978-3-031-48325-7_16.
[57] Fasihuddin, H., 2016. Enhancing open learning environments (OLEs) using adaptive
technologies and learning theories. PhD. University of Newcastle. URL http://hdl.
handle.net/1959.13/1321306.
[58] Fedoruk, P.I., 2009. Adaptive system of distance learning and knowledge control
on the basis of intelligent Internet technologies. Thesis for a Doctor’s of Technical Science degree in speciality 05.13.06 – information technologies. Institute
of mathematical machines and systems problems of NAS of Ukraine, Kyiv. URL
https://nrat.ukrintei.ua/searchdoc/0510U000090.
[59] Fidalgo-Blanco, A., Garcia-Penalvo, F.J., Sein-Echaluce, M.L. and Conde-Gonzalez,
M.A., 2014. Learning content management systems for the definition of adaptive learning environments. In: J.L. Sierra-Rodriguez, J.M. Dodero-Beardo and
D. Burgos, eds. 2014 International Symposium on Computers in Education, SIIE
2014. Institute of Electrical and Electronics Engineers Inc., pp.105–110. URL
https://doi.org/10.1109/SIIE.2014.7017713.
[60] Fielder, P.J., 1995. A Comparison of the Effectiveness of Computer Adaptive Testing
and Computer Administered Testing. PhD thesis. University of North Texas. URL
https://digital.library.unt.edu/ark:/67531/metadc279192/.
[61] Fiqri, M. and Nurjanah, D., 2017. Graph-based domain model for adaptive learning
path recommendation. IEEE Global Engineering Education Conference, EDUCON.
IEEE Computer Society, pp.375–380. URL https://doi.org/10.1109/EDUCON.2017.
7942875.
[62] Gasparinatou, A. and Grigoriadou, M., 2011. ALMA: An Adaptive Learning Models environment from texts and Activities that improves students’ science comprehension. Procedia - Social and Behavioral Sciences. vol. 15, pp.2742–2747. URL
https://doi.org/10.1016/j.sbspro.2011.04.181.
[63] Gavrilovic, N., Arsi ´ c, A., Domazet, D. and Mishra, A., 2018. Algorithm for adaptive ´
learning process and improving learners’ skills in Java programming language.
Computer Applications in Engineering Education, 26(5), pp.1362–1382. URL https://doi.org/10.1002/cae.22043.
[64] Ghaban, W.H., 2020. Adapting gamification elements to learners’ personality dimensions. Ph.D. thesis. University of Birmingham. URL http://etheses.bham.ac.
uk//id/eprint/11053/7/Ghaban2020PhD.pdf.
[65] Graf, S., Lin, F., Kinshuk and McGreal, R., 2011. Intelligent and adaptive learning
systems: Technology enhanced support for learners and teachers. Hershey, PA: IGI
Global. URL https://doi.org/10.4018/978-1-60960-842-2.
[66] Grother, T.W., 2019. Response to ‘crowdsourcing for assessment items to support
adaptive learning’. Medical Teacher, 41(7), pp.848–849. URL https://doi.org/10.
1080/0142159X.2018.1544419.
[67] Hardy, I., Hertel, S., Kunter, M., Klieme, E., Warwas, J., Buttner, G. and Luhken, ¨
A., 2011. Adaptive learning opportunities in elementary school: Characteristics,
methodological-didactic emphases, and required teacher competences [Adaptive
Lerngelegenheiten in der Grundschule: Merkmale, methodisch-didaktische Schwerpunktsetzungen und erforderliche Lehrerkompetenzen]. Zeitschrift fur Padagogik, 57(6), pp.819–833. URL https://doi.org/10.25656/01:8783.
[68] Hardy, M., Wiebe, E.N., Grafsgaard, J.F., Boyer, K.E. and Lester, J.C., 2013. Physiological Responses to Events during Training: Use of Skin Conductance to Inform Future Adaptive Learning Systems. Proceedings of the Human Factors and
Ergonomics Society Annual Meeting, 57(1), pp.2101–2105. URL https://doi.org/10.
1177/1541931213571468.
[69] Heffernan, N.T., Ostrow, K.S., Kelly, K., Selent, D., Van Inwegen, E.G., Xiong, X.
and Williams, J.J., 2016. The Future of Adaptive Learning: Does the Crowd Hold
the Key? International Journal of Artificial Intelligence in Education, 26(2), pp.615–
644. URL https://doi.org/10.1007/s40593-016-0094-z.
[70] Heiyanthuduwage, S.R., Schwitter, R. and Orgun, M.A., 2013. An adaptive learning
system using plug and play ontologies. Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2013. pp.429–
434. URL https://doi.org/10.1109/TALE.2013.6654476.
[71] Henseler, J., 2017. ADANCO 2.0.1 User Manual. URL https://ris.utwente.nl/ws/
portalfiles/portal/5135104/ADANCO_2-0-1.pdf.
[72] Henseler, J., 2021. Composite-Based Structural Equation Modeling: Analyzing Latent
and Emergent Variables, Methodology in the Social Sciences. New York, London:
The Guilford Press.
[73] Hertel, S., Warwas, J. and Klieme, E., 2011. Individual fostering and adaptive learning opportunities in elementary school instruction. An introduction [Individuelle Forderung und adaptive Lerngelegenheiten im Grundschulunterricht. Ein- ¨
leitung in den Thementeil]. Zeitschrift fur Padagogik, 57(6), pp.803–804. URL
https://www.fachportal-paedagogik.de/literatur/vollanzeige.html?FId=3146197.
[74] Hou, M. and Fidopiastis, C., 2017. A generic framework of intelligent adaptive learning systems: from learning effectiveness to training transfer. Theoretical Issues in Ergonomics Science, 18(2), pp.167–183. URL https://doi.org/10.1080/
1463922X.2016.1166405.
[75] How, M.L. and Hung, W.L.D., 2019. Educational Stakeholders’ independent
evaluation of an artificial intelligence-enabled adaptive learning system using
bayesian network predictive simulations. Education Sciences, 9(2), p.110. URL
https://doi.org/10.3390/educsci9020110.
[76] Hu, Q. and Huang, Y., 2014. An approach for designing test bank in adaptive
learning system. Proceedings of the 9th International Conference on Computer Science and Education, ICCCSE 2014. Institute of Electrical and Electronics Engineers
Inc., pp.462–464. URL https://doi.org/10.1109/ICCSE.2014.6926504.
[77] Huang, L.H., Dow, C.R., Li, Y.H. and Hsuan, P., 2013. U-TA: A ubiquitous teaching
assistant using knowledge retrieval and adaptive learning techniques. Computer
Applications in Engineering Education, 21(2), pp.245–255. URL https://doi.org/10.
1002/cae.20466.
[78] Huang, S.L. and Shiu, J.H., 2012. A user-centric adaptive learning system for elearning 2.0. Educational Technology and Society, 15(3), pp.214–225. URL https:
//www.researchgate.net/publication/285724853.
[79] Huang, X., Yang, K. and Lawrence, V., 2015. Classification-based approach to
concept map generation in adaptive learning. In: N.S. Chen, T.C. Liu, Kinshuk, R. Huang, G.J. Hwang, D.G. Sampson and C.C. Tsai, eds. Proceedings -
IEEE 15th International Conference on Advanced Learning Technologies: Advanced
Technologies for Supporting Open Access to Formal and Informal Learning, ICALT
2015. Institute of Electrical and Electronics Engineers Inc., pp.19–23. URL https:
//doi.org/10.1109/ICALT.2015.149.
[80] Huffman, M., Gustafson, S., Chatterjee, S., Rabner, M., Nundy, S., Gerkovich, M.M.
and Wright, S.M., 2018. Bolstering diagnostic reasoning skills with adaptive learning. Medical Teacher, 40(8), pp.845–849. URL https://doi.org/10.1080/0142159x.
2018.1484561.
[81] Hwang, G.J., Sung, H.Y., Hung, C.M. and Huang, I., 2013. A learning style perspective to investigate the necessity of developing adaptive learning systems. Educational Technology and Society, 16(2), pp.188–197. URL https://www.researchgate.
net/publication/279711154.
[82] Ham¨ al¨ ainen, W., Kumpulainen, V. and Mozgovoy, M., 2014. Evaluation of cluster- ¨
ing methods for adaptive learning systems. In: U. Kose and D. Koc, eds. Artificial
Intelligence Applications in Distance Education. Hershey, PA: IGI Global, pp.237–
260. URL https://doi.org/10.4018/978-1-4666-6276-6.ch014.
[83] Ibrahim, M.S. and Hamada, M., 2016. Adaptive learning framework. 2016
15th International Conference on Information Technology Based Higher Education
and Training, ITHET 2016. Institute of Electrical and Electronics Engineers Inc.,
p.7760738. URL https://doi.org/10.1109/ITHET.2016.7760738.
[84] Idrobo, C.J. and Davidson-Hunt, I.J., 2012. Adaptive learning, technological innovation and livelihood diversification: The adoption of pound nets in Rio de
Janeiro state, Brazil. Maritime Studies, 11(1), pp.1–22. URL https://doi.org/10.
1186/2212-9790-11-3.
[85] Indrayadi, F. and Nurjanah, D., 2015. Combining learner’s preference and similar
peers’ experience in adaptive learning. In: M. Helfert, M.T. Restivo, S. Zvacek
and J. Uhomoibhi, eds. CSEDU 2015 - 7th International Conference on Computer
Supported Education, Proceedings. SciTePress, vol. 1, pp.486–493. URL https://doi.
org/10.5220/0005490904860493.
[86] Isaksson, E., Naeve, A. and Lefrere, P., 2016. Performance Augmentation Through `
Ubiquitous and Adaptive Learning and Work Environments. In: Y. Li, M. Chang,
M. Kravcik, E. Popescu, R. Huang, Kinshuk and N.S. Chen, eds. State-of-the-Art and
Future Directions of Smart Learning. Singapore: Springer Singapore, pp.315–319.
URL https://doi.org/10.1007/978-981-287-868-7_39.
[87] Iyer, S.S., Gernal, L., Subramanian, R. and Mehrotra, A., 2023. Impact of digital
disruption influencing business continuity in UAE higher education. Educational
Technology Quarterly, 2023(1), p.18–57. URL https://doi.org/10.55056/etq.29.
[88] Jiang, S., 2020. On-The-Fly Parameter Estimation Based on Item Response Theory in
Item-based Adaptive Learning Systems. PhD, Psychology. University of Minnesota.
URL http://hdl.handle.net/11299/218710.
[89] Johnson, S. and Zaiane, O.R., 2017. Learning to Analyze Medical Images: A Smart
Adaptive Learning Environment for an Ill-Defined Domain. In: E. Popescu, Kinshuk, M.K. Khribi, R. Huang, M. Jemni, N.S. Chen and D.G. Sampson, eds. Innovations in Smart Learning. Singapore: Springer Singapore, pp.103–112. URL
https://doi.org/10.1007/978-981-10-2419-1_15.
[90] Johnson, Z., 2016. Teachers as designers of context-adaptive learning experience.
In: S. Goldman and Z. Kabayadondo, eds. Taking Design Thinking to School: How
the Technology of Design Can Transform Teachers, Learners, and Classrooms. Taylor
and Francis, pp.126–142. URL https://doi.org/10.4324/9781317327585.
[91] Jonsdottir, A.H., Jakobsdottir, A. and Stefansson, G., 2015. Development and use
of an adaptive learning environment to research online study behaviour. Educational Technology and Society, 18(1), pp.132–144. URL https://www.researchgate.
net/publication/282378459.
[92] Jordan, C., 2013. Comparison of International Baccalaureate (IB) chemistry students’ preferred vs actual experience with a constructivist style of learning in a
Moodle e-learning environment. International Journal for Lesson and Learning
Studies, 2(2), p.155–167. URL https://doi.org/10.1108/20468251311323397.
[93] Kabudi, T., Pappas, I. and Olsen, D.H., 2021. AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial
Intelligence, 2, p.100017. URL https://doi.org/10.1016/j.caeai.2021.100017.
[94] Kaensar, C. and Wongnin, W., 2023. Analysis and Prediction of Student Performance Based on Moodle Log Data using Machine Learning Techniques. International Journal of Emerging Technologies in Learning. vol. 18, pp.184 – 203. URL
https://doi.org/10.3991/ijet.v18i10.35841.
[95] Kakish, K. and Pollacia, L., 2018. Adaptive learning to improve student success
and instructor efficiency in introductory computing course. In: B.L. Garner, ed.
Proceedings of the 34th Information Systems Education Conference, ISECON 2018.
Foundation for Information Technology Education, pp.72–78. URL https://www.
researchgate.net/publication/324574230.
[96] Kakish, K., Robertson, C. and Jonassen, L., 2019. Understanding perceptions
of conceptual information technology adaptive learning. In: B.L. Garner, ed.
Proceedings of the Information Systems Education Conference, ISECON. Foundation for Information Technology Education, vol. 2019-April, pp.47–54. URL http:
//proceedings.isecon.org/download/howeebs8i9p1d9jophtt.
[97] Kakosimos, K.E., 2015. Example of a micro-adaptive instruction methodology for
the improvement of flipped-classrooms and adaptive-learning based on advanced
blended-learning tools. Education for Chemical Engineers, 12, pp.1–11. URL https:
//doi.org/10.1016/j.ece.2015.06.001.
[98] Kardan, A., Imani, M.B. and Ebrahim, M.A., 2013. A novel adaptive learning path
method. 4th International Conference on e-Learning and e-Teaching, ICELET 2013.
pp.20–25. URL https://doi.org/10.1109/ICELET.2013.6681639.
[99] Kaw, A., Clark, R., Delgado, E. and Abate, N., 2019. Analyzing the use of adaptive
learning in a flipped classroom for preclass learning. Computer Applications in
Engineering Education, 27(3), pp.663–678. URL https://doi.org/10.1002/cae.22106.
[100] Kellman, P.J. and Krasne, S., 2018. Accelerating expertise: Perceptual and adaptive
learning technology in medical learning. Medical Teacher, 40(8), pp.797–802. URL
https://doi.org/10.1080/0142159X.2018.1484897.
[101] Kerr, P., 2016. Adaptive learning. ELT Journal, 70(1), pp.88–93. URL https://doi.
org/10.1093/elt/ccv055.
[102] Krahn, T., Kuo, R. and Chang, M., 2023. Personalized Study Guide: A Moodle Plugin Generating Personal Learning Path for Students. In: C. Frasson, P. Mylonas
and C. Troussas, eds. Lecture Notes in Computer Science (including subseries Lecture
Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Science
and Business Media Deutschland GmbH, vol. 13891 LNCS, pp.333 – 341. URL
https://doi.org/10.1007/978-3-031-32883-1_30.
[103] Kuzikov, B.O., 2014. Information technology of analysis and synthesis of adaptive e-learning system. The dissertation on competition of a scientific degree of a
Cand.Tech.Sci on a specialty 05.13.06 – information technology. National Technical University “Kharkiv Polytechnic Institute”’, Kharkiv. URL https://nrat.ukrintei.
ua/searchdoc/0414U003734.
[104] Kyrychenko, I.V., 2019. Information technology of content identification in adaptive
e-learning systems. Dissertation for the degree of a candidate of technical sciences in specialty 05.13.06 – «Information technologies». Kremenchuk Mykhailo
Ostrohradskyi National University, Kremenchuk. URL https://nrat.ukrintei.ua/
searchdoc/0419U002452.
[105] Lai, K.R., Chou, C.Y. and Lan, C.H., 2012. Supporting adaptive learning sequences
with agent negotiation. Proceedings of the 12th IEEE International Conference on
Advanced Learning Technologies, ICALT 2012. pp.506–508. URL https://doi.org/10.
1109/ICALT.2012.26.
[106] Laitinen, I., Piazza, R. and Stenvall, J., 2017. Adaptive learning in smart cities –
The cases of Catania and Helsinki. Journal of Adult and Continuing Education,
23(1), pp.119–137. URL https://doi.org/10.1177/1477971417691781.
[107] Lestari, W., Nurjanah, D. and Selviandro, N., 2017. Adaptive presentation based
on learning style and working memory capacity in adaptive learning system. In: P. Escudeiro, S. Zvacek, B.M. McLaren, J. Uhomoibhi and G. Costagliola, eds.
CSEDU 2017 - Proceedings of the 9th International Conference on Computer Supported Education. SciTePress, vol. 1, pp.363–370. URL https://www.researchgate.
net/publication/320699853.
[108] Levy, J.C., 2015. Adaptive Learning and the Human Condition. Taylor and Francis.
URL https://doi.org/10.4324/9781315665160.
[109] Li, H., Cui, W., Xu, Z., Zhu, Z. and Feng, M., 2018. Yixue adaptive learning system and its promise on improving student learning. In: B.M. McLaren, R. Reilly,
S. Zvacek and J. Uhomoibhi, eds. CSEDU 2018 - Proceedings of the 10th International Conference on Computer Supported Education. SciTePress, vol. 2, pp.45–52.
URL https://doi.org/10.5220/0006689800450052.
[110] Li, R., 2019. Adaptive learning model based on ant colony algorithm. International
Journal of Emerging Technologies in Learning, 14(1), pp.49–57. URL https://doi.org/
10.3991/ijet.v14i01.9487.
[111] Li, Y.H., Zhao, B. and Gan, J.H., 2015. Make adaptive learning of the MOOC: The
CML model. 10th International Conference on Computer Science and Education,
ICCSE 2015. Institute of Electrical and Electronics Engineers Inc., pp.1001–1004.
URL https://doi.org/10.1109/ICCSE.2015.7250398.
[112] Li, Z., Yang, Y., Wu, Y. and Jia, J., 2013. An adaptive Learning system based on
the case. Proceedings of the 8th International Conference on Computer Science and
Education, ICCSE 2013. pp.1431–1435. URL https://doi.org/10.1109/ICCSE.2013.
6554150.
[113] Lin, C.C. and Wu, Y.T., 2018. The effectiveness of integrating adaptive learning platform with flipped classroom in students’ learning performance and selflearning approach. In: L.H. Wong, M. Banawan, N. Srisawasdi, J.C. Yang, M.M.T. Rodrigo, M. Chang and Y.T. Wu, eds. ICCE 2018 - 26th International Conference on
Computers in Education, Workshop Proceedings. Asia-Pacific Society for Computers in Education, pp.304–308. URL https://scholars.ncu.edu.tw/en/publications/
the-effectiveness-of-integrating-adaptive-learning-platform-with-.
[114] Lin, C.C., Wu, Y.T. and Cheng, T.Y., 2017. Online knowledge-structurebased adaptive science learning: Integrates adaptive dynamic assessment
into adaptive learning. In: T. Hayashi Y. amd Supnithi, M. Mathews, S.L. Wong, A.F. Mohd Ayub, A. Mitrovic, W. Chen and J.C. Yang,
eds. ICCE 2017 - 25th International Conference on Computers in Education: Technology and Innovation: Computer-Based Educational Systems for
the 21st Century, Workshop Proceedings. Asia-Pacific Society for Computers
in Education, pp.595–600. URL https://scholars.ncu.edu.tw/en/publications/
online-knowledge-structure-based-adaptive-science-learning-integr.
[115] Linden, K., Webster, L., Pemberton, L. and Davison, W.R., 2017. Can we calm
first-year student’s “neuroscience anxiety” with adaptive learning resources? A
pilot study. In: S. Krishnan, S. Macfarlane, L. Ngo, J. Tai, D. Blake, I. Doherty, I. Story, M. Campbell, J. Willems, C. Adachi, S. Palmer, M. O’Donnell,
L. Riddell and H. Suri, eds. ASCILITE 2018 - Conference Proceedings - 35th International Conference of Innovation, Practice and Research in the use of Educational Technologies in Tertiary Education: Open Oceans: Learning Without
Borders. Australasian Society for Computers in Learning in Tertiary Education
(ASCILITE), pp.451–455. URL https://researchoutput.csu.edu.au/en/publications/
can-we-calm-first-year-students-neuroscience-anxiety-with-adaptiv.
[116] Lishon-Savarino, N.A., 2017. A Conspectus review of adaptive learning technology’s instructional design techniques for developmental mathematics using Gagne’s nine events of instruction. In: P. Roubides, ed. ´ Distance Learning: Perspectives, Outcomes and Challenges. Nova Science Publishers, Inc., Education in a
Competitive and Globalizing World, pp.147–164.
[117] Liu, M., Kang, J., Zou, W., Lee, H., Pan, Z. and Corliss, S., 2017. Using Data to
Understand How to Better Design Adaptive Learning. Technology, Knowledge and
Learning, 22(3), pp.271–298. URL https://doi.org/10.1007/s10758-017-9326-z.
[118] Liu, M., McKelroy, E., Corliss, S. and Carrigan, J., 2017. Investigating the effect
of an adaptive learning intervention on students’ learning. Educational Technology Research and Development, 65(6), pp.1605–1625. URL https://doi.org/10.1007/
s11423-017-9542-1.
[119] Martinez, D.V., Shafik, R.A., Acharyya, A. and Merrett, G., 2016. Design and implementation of an adaptive learning system: An MSc project experience. 2016
11th European Workshop on Microelectronics Education, EWME 2016. Institute of
Electrical and Electronics Engineers Inc., p.7496481. URL https://doi.org/10.1109/
EWME.2016.7496481.
[120] Martynova, Y.V., 2011. Informational technologies of adaptive computerized system
for teaching and testing. Dissertation for proving the master degree of scientific
branch 05.13.06 – information technologies. Kherson National Technical University, Kherson. URL https://nrat.ukrintei.ua/searchdoc/0412U001155.
[121] Massey, C.M., Kellman, P.J., Roth, Z. and Burke, T., 2013. Perceptual learning and adaptive learning technology: Developing new approaches to mathematics learning in the classroom. Taylor and Francis. URL https://doi.org/10.1007/
978-3-030-95633-2_5.
[122] Matar, N., 2011. Adaptive Learning Objects Repository structure towards unified
e-learning. International Conference on Information Society, i-Society 2011. IEEE Computer Society, pp.404–410. URL https://doi.org/10.1109/i-society18435.2011.
5978480.
[123] Matthews, K., Janicki, T., He, L. and Patterson, L., 2012. Implementation of an
automated grading system with an adaptive learning component to affect student feedback and response time. Journal of Information Systems Education, 23(1),
pp.71–80. URL https://aisel.aisnet.org/jise/vol23/iss1/7.
[124] Mavroudi, A., Giannakos, M. and Krogstie, J., 2016. Insights on the interplay
between adaptive learning and learning analytics. In: J.M. Spector, C.C. Tsai,
R. Huang, P. Resta, D.G. Sampson, Kinshuk and N.S. Chen, eds. Proceedings -
IEEE 16th International Conference on Advanced Learning Technologies, ICALT
2016. Institute of Electrical and Electronics Engineers Inc., pp.42–43. URL https:
//doi.org/10.1109/ICALT.2016.84.
[125] Mavroudi, A., Giannakos, M. and Krogstie, J., 2018. Supporting adaptive learning
pathways through the use of learning analytics: developments, challenges and
future opportunities. Interactive Learning Environments, 26(2), pp.206–220. URL
https://doi.org/10.1080/10494820.2017.1292531.
[126] Mavroudi, A., Hadzilacos, T., Kalles, D. and Gregoriades, A., 2016. Teacher-led
design of an adaptive learning environment. Interactive Learning Environments,
24(8), pp.1996–2010. URL https://doi.org/10.1080/10494820.2015.1073747.
[127] Mazurets, O.V., 2020. Information Technology for Automated Structuring of Educational Materials and Creation of Tests for Adaptive Control of the Level of Knowledge.
The thesis for the degree of candidate of technical sciences, specialty 05.13.06 «Information technology». Ternopil National Economic University, Ternopil. URL
https://nrat.ukrintei.ua/searchdoc/0420U101209.
[128] Mccaslin, M. and Burross, H.L., 2011. Research on individual differences within a sociocultural perspective: Co-regulation and adaptive learning. Teachers College
Record, 113(2), pp.325–349. URL https://doi.org/10.1177/016146811111300203.
[129] Mehigan, T.J., 2013. Automatic detection of learner-style for adaptive eLearning.
PhD thesis. University College Cork. URL http://hdl.handle.net/10468/1334.
[130] Mei, J., Guo, Y. and Li, X., 2017. Adaptive Learning Mode of a Multimedia-based
“English Literature” Learning System . International Journal of Emerging Technologies in Learning, 12(1), pp.71–83. URL https://doi.org/10.3991/ijet.v12i01.6483.
[131] Menon, A., Gaglani, S., Haynes, M. and Tackett, S., 2017. Using “big data” to guide
implementation of a web and mobile adaptive learning platform for medical students. Medical Teacher, 39(9), pp.975–980. URL https://doi.org/10.1080/0142159X.
2017.1324949.
[132] Midgley, C., 2014. Goals, Goal Structures, and Patterns of Adaptive Learning. Taylor
and Francis. URL https://doi.org/10.4324/9781410602152.
[133] Miller, L.A., Asarta, C.J. and Schmidt, J.R., 2019. Completion deadlines, adaptive
learning assignments, and student performance. Journal of Education for Business,
94(3), pp.185–194. URL https://doi.org/10.1080/08832323.2018.1507988.
[134] Ministry of Education and Science of Ukraine, 2018. Nakaz pro zatverdzhennia Kontseptsii rozvytku pedahohichnoi osvity [Order on approval of the Concept of pedagogical education development]. URL https://mon.gov.ua/ua/npa/
pro-zatverdzhennya-koncepciyi-rozvitku-pedagogichnoyi-osviti.
[135] Minkovska, D., Ivanova, M. and Yordanova, M., 2016. Didactic principles of
eLearning -Design and implementation of an interactive adaptive learning system. 2016 15th International Conference on Information Technology Based Higher
Education and Training, ITHET 2016. Institute of Electrical and Electronics Engineers Inc., p.7760709. URL https://doi.org/10.1109/ITHET.2016.7760709.
[136] Mirata, V. and Bergamin, P., 2019. Developing an implementation framework for
adaptive learning: A case study approach. In: R. Orngreen, M. Buhl and B. Meyer,
eds. Proceedings of the European Conference on e-Learning, ECEL. Academic Conferences Limited, vol. 2019-November, pp.668–673. URL https://doi.org/10.34190/
EEL.19.024.
[137] Miyagi, T., 2011. An adaptive learning algorithm for a route choice problem in
uncertain traffic environments. WIT Transactions on the Built Environment. vol.
116, pp.43–52. URL https://doi.org/10.2495/UT110041.
[138] Moreno-Marcos, P.M., Barredo, J., Munoz-Merino, P.J. and Delgado Kloos, C., ˜
2023. Statoodle: A Learning Analytics Tool to Analyze Moodle Students’ Actions
and Prevent Cheating. In: O. Viberg, I. Jivet, P.J. Munoz-Merino, M. Perifanou ˜
and T. Papathoma, eds. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer
Science and Business Media Deutschland GmbH, vol. 14200 LNCS, pp.736 – 741.
URL https://doi.org/10.1007/978-3-031-42682-7_70.
[139] Nakic, J., Granic, A. and Glavinic, V., 2015. Anatomy of student models in adaptive
learning systems: A systematic literature review of individual differences from
2001 to 2013. Journal of Educational Computing Research, 51(4), pp.459–489. URL
https://doi.org/10.2190/EC.51.4.e.
[140] Nasr-Eddine, B.S., Zaidi, S. and Eddine, Z.N., 2012. An architecture of an adaptive
learning system. 2012 International Conference on Education and e-Learning Innovations, ICEELI 2012. p.6360622. URL https://doi.org/10.1109/ICEELI.2012.6360622.
[141] Natriello, G., 2017. The adaptive learning landscape. Teachers College Record,
119(3), p.030309. URL https://doi.org/10.1177/01614681171190030.
[142] Natriello, G. and Chae, H.S., 2017. Introduction to the special issue on adaptive learning opportunities. Teachers College Record, 119(3), p.030301. URL https://doi.
org/10.1177/016146811711900304.
[143] Nesterova, M., 2015. Informatsiino-kohnityvni tekhnolohii v systemi vyshchoi
osvity suspilstva znan. Vyshcha osvita Ukrainy, (1), pp.40–45. URL http://nbuv.
gov.ua/UJRN/vou_2015_1_7.
[144] Nesterova, M.O., 2015. Modern Cognitive Researches: Philosophical-methodological
Conceptualisation Contexts. Thesis for the degree of Doctor of Sciences in Philosophy, Speciality 09.00.09 – Philosophy of Science. Taras Shevchenko National
University of Kyiv, Kyiv. URL https://nrat.ukrintei.ua/searchdoc/0516U000888.
[145] Nguyen, L., 2014. A user modeling system for adaptive learning. Proceedings
of 2014 International Conference on Interactive Collaborative Learning, ICL 2014.
Institute of Electrical and Electronics Engineers Inc., pp.864–866. URL https://doi.
org/10.1109/ICL.2014.7017887.
[146] Nguyen, V.A., 2012. Toward an adaptive learning system framework: Using
bayesian network to manage learner model. International Journal of Emerging
Technologies in Learning, 7(4), pp.38–47. URL https://doi.org/10.3991/ijet.v7i4.
2290.
[147] Nurjanah, D., 2014. The granularity of collaborative work for creating adaptive
learning resources. CSEDU 2014 - Proceedings of the 6th International Conference
on Computer Supported Education. SciTePress, vol. 1, pp.165–173. URL https://doi.
org/10.5220/0004722701650173.
[148] Nurjanah, D., 2016. Good and similar learners’ recommendation in adaptive learning systems. In: J. Uhomoibhi, G. Costagliola, S. Zvacek and B.M. McLaren,
eds. CSEDU 2016 - Proceedings of the 8th International Conference on Computer
Supported Education. SciTePress, vol. 1, pp.434–440. URL https://doi.org/10.5220/0005864304340440.
[149] Nurjanah, D., 2018. LifeOn, a ubiquitous lifelong learner model ontology supporting adaptive learning. IEEE Global Engineering Education Conference, EDUCON.
IEEE Computer Society, vol. 2018-April, pp.866–871. URL https://doi.org/10.1109/
EDUCON.2018.8363321.
[150] Nussbaumer, A., Steiner, C.M., Hillemann, E.C. and Albert, D., 2014. Towards
an evaluation service for adaptive learning systems. In: H. Ogata, L. LomickaAnderson, C.S. Chai, R. Hampel, Y. Hayashi, J. Vassileva, C.C. Liu, W. Chen, J. Hsu,
Y.J. Lan, J. Mason, M. Yamada, H.Y. Shyu, A. Weerasinghe, Y.T. Wu, L. Zhang, Kinshuk, Y. Matsubara, Y. Miao, H. Ogata, S.C. Kong, M. Chang, M.S.Y. Jong, R. Kuo,
R. Robson, B. Wasson, A. Kashihara, U. Cress, M. Jansen, J. Oshima, C. Yin, J. Zhang
and C. Chinn, eds. Proceedings of the 22nd International Conference on Computers
in Education, ICCE 2014. Asia-Pacific Society for Computers in Education, pp.138–
140. URL https://www.researchgate.net/publication/289630492.
[151] Nye, B.D., Pavlik, P. I., J., Windsor, A., Olney, A.M., Hajeer, M. and Hu, X., 2018.
SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): overlaying natural language tutoring on an adaptive learning system for mathematics.
International Journal of STEM Education, 5(1), p.12. URL https://doi.org/10.1186/
s40594-018-0109-4.
[152] Obikwelu, C. and Read, J., 2013. Serious game adaptive learning systems. 7th
European Conference on Games Based Learning, ECGBL 2013. vol. 2, pp.442–449.
URL https://issuu.com/acpil/docs/ecgbl2013-issuu_vol_2.
[153] Oke, I., Kulkarni, P., Lolap, T. and Haribhakta, Y., 2017. Adaptive Learning System for Analysis of Performance and Learning Behavior of School Children. In:
V. Kumar, Kinshuk and S. Murthy, eds. Proceedings - IEEE 8th International Conference on Technology for Education, T4E 2016. Institute of Electrical and Electronics
Engineers Inc., pp.238–239. URL https://doi.org/10.1109/T4E.2016.058.
[154] Oliveira, E.H.T., Nozawa, E.H., Costa, L.F., Vicari, R.M. and Albuquerque, Y.C.,
2012. Work in progress: Towards a framework for adaptive learning systems.
Proceedings - Frontiers in Education Conference, FIE. p.6462239. URL https://doi.
org/10.1109/FIE.2012.6462239.
[155] Osadchyi, V.V., 2023. Adaptive system for individualization and personalization
of professional training of future specialists in blended learning. (0223U003360).
Bogdan Khmelnitsky Melitopol State Pedagogical University. URL https://nrat.
ukrintei.ua/searchdoc/0223U003360.
[156] Osadchyy, V.V., 2020. Adaptyvna systema dlia indyvidualizatsii ta personalizatsii profesiinoi pidhotovky maibutnikh fakhivtsiv v umovakh zmishanoho navchannia (promizhnyi) [Adaptive system for individualization and personalization of professional training of future specialists in conditions of mixed learning (interim)].
(0221U101936). Melitopol State Pedagogical University. URL https://nrat.ukrintei.
ua/searchdoc/0221U101936.
[157] Osadchyy, V.V., 2022. Adaptyvna systema dlia indyvidualizatsii ta personalizatsii profesiinoi pidhotovky maibutnikh fakhivtsiv v umovakh zmishanoho navchannia (promizhnyi) [Adaptive system for individualization and personalization of professional training of future specialists in conditions of mixed learning (interim)].
(0222U000480). Melitopol State Pedagogical University. URL https://nrat.ukrintei.
ua/searchdoc/0222U000480.
[158] Palomino, C.E.G., Silveira, R.A. and Nakayama, M.K., 2015. Using agent-based
adaptive learning environments for knowledge sharing management. International Journal of Knowledge and Learning, 10(3), pp.278–295. URL https://doi.org/10.1504/IJKL.2015.073475.
[159] Panicker, R.C., Kumar, A., Srinivasan, D. and John, D., 2019. Adaptive Learning
and Analytics in Engineering Education. In: M.J.W. Lee, S. Nikolic, G.K.W. Wong,
J. Shen, M. Ros, L.C.U. Lei and N. Venkatarayalu, eds. Proceedings of 2018 IEEE
International Conference on Teaching, Assessment, and Learning for Engineering,
TALE 2018. Institute of Electrical and Electronics Engineers Inc., pp.1193–1196.
URL https://doi.org/10.1109/TALE.2018.8615200.
[160] Pedan, S.I., 2012. Models and methods of information technology of competenceoriented adaptive tutoring support. Thesis for candidate of technical sciences. degree on the specialty 05.13.06 — information technologies. National Aerospace
University “Kharkiv Aviation Institute”, Kharkiv. URL https://nrat.ukrintei.ua/
searchdoc/0412U003745.
[161] Pelanek, R., 2018. Exploring the utility of response times and wrong answers for ´
adaptive learning. Proceedings of the Fifth Annual ACM Conference on Learning at
Scale. New York, NY, USA: Association for Computing Machinery, L@S ’18, p.18.
URL https://doi.org/10.1145/3231644.3231675.
[162] Peng, H., Ma, S. and Spector, J.M., 2019. Personalized Adaptive Learning: An
Emerging Pedagogical Approach Enabled by a Smart Learning Environment. In:
M. Chang, E. Popescu, Kinshuk, N.S. Chen, M. Jemni, R. Huang, J.M. Spector and
D.G. Sampson, eds. Foundations and Trends in Smart Learning. Singapore: Springer,
Lecture Notes in Educational Technology, pp.171–176. URL https://doi.org/10.
1007/978-981-13-6908-7_24.
[163] Perez-Suay, A., Van Vaerenbergh, S., Diago, P.D., Pascual-Venteo, A.B. and Ferri,
F.J., 2023. Data-Driven Modeling Through the Moodle Learning Management
System: An Empirical Study Based on a Mathematics Teaching Subject. Revista Iberoamericana de Tecnologias del Aprendizaje. Education Society of IEEE (Spanish
Chapter), vol. 18, pp.19 – 27. URL https://doi.org/10.1109/RITA.2023.3250434.
[164] Philosophy, 2006. URL https://web.archive.org/web/20060901040155/http://docs.
moodle.org/en/Philosophy.
[165] Pikulyak, M.V., 2016. Methods and tools for forming of adaptive system of distance education. The thesis for the degree of candidate of technical sciences, specialty 05.13.06 – information technologies. Ternopil National Economic University, Ternopil. URL http://dspace.wunu.edu.ua/handle/316497/4531.
[166] Pliakos, K., Joo, S.H., Park, J.Y., Cornillie, F., Vens, C. and Noortgate, W. Van den,
2019. Integrating machine learning into item response theory for addressing the
cold start problem in adaptive learning systems. Computers and Education, 137,
pp.91–103. URL https://doi.org/10.1016/j.compedu.2019.04.009.
[167] Pogrebniuk, I.M., 2013. Modelling of the adaptive learning scenarios with the use
of Petri nets. Dissertation thesis for the degree of candidate of technical sciences,
speciality 05.13.06 – information technologies. National Transport University,
Kyiv. URL https://nrat.ukrintei.ua/searchdoc/0413U002243.
[168] Qu, Y., Cai, R. and Haj-Hussein, M., 2019. Research and Practice of Applying Adaptive Learning in Computer Science and IT Degree Programs. Proceedings - Frontiers
in Education Conference, FIE. Institute of Electrical and Electronics Engineers Inc.,
vol. 2019-October, p.9028374. URL https://doi.org/10.1109/FIE43999.2019.9028374.
[169] Quispe-Pari, E., Tamo-Vargas, G., Bedregal-Alpaca, N., Guevara, K., DelgadoBarra, L. and Laura-Ochoa, L., 2023. Adaptability in Moodle, Case:
Grading restrictions; [Adaptabilidad en Moodle, Caso: Restricciones en
las calificaciones]. RISTI - Revista Iberica de Sistemas e Tecnologias de
Informacao. Associacao Iberica de Sistemas e Tecnologias de Informacao, vol. 2023, pp.195 – 208. URL https://pure.unsa.edu.pe/en/publications/
adaptabilidad-en-moodle-caso-restricciones-en-las-calificaciones.
[170] Regulation on the system of assessment of the students’ learning outcomes
in the Kryvyi Rih State Pedagogical University [Polozhennia pro systemu
otsiniuvannia navchalnykh dosiahnen studentiv u Kryvorizkomu derzhavnomu
pedahohichnomu universyteti], 2022. URL https://drive.google.com/file/d/
1DIvAyjUfmbqj93eqLJfHcYmNlJ3mx24t/view.
[171] Regulation on using the distance learning technologies in the educational activity of the Kryvyi Rih State Pedagogical University [Polozhennia pro vykorystannia tekhnolohii dystantsiinoho navchannia v osvitnii diialnosti Kryvorizkoho
derzhavnoho Pedahohichnoho universytetu], 2021. URL https://drive.google.com/
file/d/1VxVOH3vSMeq6vLXdAKZzHonmcKa2jw97/view.
[172] Rimbaud, Y., McEwan, T., Lawson, A. and Cairncross, S., 2015. Adaptive learning
in computing for non-native speakers. Proceedings - Frontiers in Education Conference, FIE. Institute of Electrical and Electronics Engineers Inc., vol. 2015-February,
p.7044142. URL https://doi.org/10.1109/FIE.2014.7044142.
[173] Rodrigues Pereira, J.C., Dos Anjos Formiga Cabral, L., Dos Santos Oiveira, R., Bezerra, L.L. and De Melo, N.M.T., 2012. OAEditor - A framework for editing adaptive learning objects. IADIS International Conference on Cognition and Exploratory
Learning in Digital Age, CELDA 2012. pp.236–240. URL https://www.iadisportal.
org/digital-library/oaeditor-a-framework-for-editing-adaptive-learning-objects.
[174] Rosen, Y., Munson, L., Lopez, G., Rushkin, I., Ang, A., Tingley, D., Rubin, R. and
Weber, G., 2018. The effects of adaptive learning in a massive open online course
on learners’ skill development. Proceedings of the 5th Annual ACM Conference on
Learning at Scale, L at S 2018. Association for Computing Machinery, Inc, p.6. URL https://doi.org/10.1145/3231644.3231651.
[175] Rudnitska, O., 2020. Information technology for the development of the continuing education adaptive system for smart industries. Dissertation for the Doctor
of Philosophy degree of technical sciences in specialty 122 "Computer Science".
Kyiv National University of Construction and Architecture of the Ministry of Education and Science of Ukraine, Kyiv. URL https://nrat.ukrintei.ua/searchdoc/
0820U100340/.
[176] Sandman, T.E., 2014. A preliminary investigation into the adaptive learning styles
of business students. Decision Sciences Journal of Innovative Education, 12(1),
pp.33–54. URL https://doi.org/10.1111/dsji.12020.
[177] Schaul, T. and LeCun, Y., 2013. Adaptive learning rates and parallelization for
stochastic, sparse, non-smooth gradients. 1st International Conference on Learning Representations, ICLR 2013 - Conference Track Proceedings. International Conference on Learning Representations, ICLR. URL https://doi.org/10.48550/arXiv.
1301.3764.
[178] Sergeev, K., Mironenko, O., Krivich, O.Y., Petrov, A. and Kozlov, M., 2023. Using
the module “analytics and machine learning” in LMS moodle at training students
of specialty “rolling stock”. In: A.G. Galkin and S.V. Bushuev, eds. AIP Conference
Proceedings. American Institute of Physics Inc., vol. 2624. URL https://doi.org/10.
1063/5.0133923.
[179] Seriakov, A. and Shcheholkova, V., 2021. Modeli ta metody v adaptyvnykh systemakh navchannia (promizhnyi) [Models and methods in adaptive learning systems (interim)]. (0221U103332). Shostkin Institute of Sumy State University. URL
https://nrat.ukrintei.ua/searchdoc/0221U103332.
[180] Serrao-Neumann, S., Cox, M. and Low Choy, D., 2019. Bridging Adaptive Learning and Desired Natural Resource Management Outcomes: Insights from Australian
Planners. Planning Practice and Research, 34(2), pp.149–167. URL https://doi.org/
10.1080/02697459.2018.1549188.
[181] Sfenrianto, S., Hartarto, Y., Akbar, H., Mukhtar, M., Efriadi, E. and Wahyudi, M.,
2018. An adaptive learning system based on knowledge level for English learning. International Journal of Emerging Technologies in Learning, 13(12), pp.191–200.
URL https://doi.org/10.3991/ijet.v13i12.8004.
[182] Sharma, C. and Jordan, R., 2019. Is adaptive learning the way forward? Medical
Teacher, 41(4), pp.484–485. URL https://doi.org/10.1080/0142159X.2018.1513644.
[183] Shelle, G., Earnesty, D., Pilkenton, A. and Powell, E., 2018. Adaptive learning: An
innovative method for online teaching and learning. Journal of Extension, 56(5),
p.17. URL https://doi.org/10.34068/joe.56.05.17.
[184] Shemshack, A., 2022. Personalized Adaptive Teacher Education to Increase SelfEfficacy: Toward a Framework for Teacher Education. PhD thesis. University of
North Texas. URL https://digital.library.unt.edu/ark:/67531/metadc1944377/.
[185] Shikano, S. and Kittel, B., 2016. Dynamics of Voting Propensity: Experimental
Tests of Adaptive Learning Models. Political Research Quarterly, 69(4), pp.813–
829. URL https://doi.org/10.1177/1065912916663654.
[186] Shyshkina, M.P., 2020. Adaptyvna khmaro oriientovana systema navchannia ta
profesiinoho rozvytku vchyteliv zakladiv zahalnoi serednoi osvity [Adaptive cloudoriented system of training and professional development of teachers of general secondary education institutions]. (0221U102106). National Academy of Pedagogical
Sciences of Ukraine. URL https://nrat.ukrintei.ua/searchdoc/0221U102106.
[187] Skuballa, I.T., Leber, J., Schmidt, H., Zimmermann, G. and Renkl, A., 2016. Using
online eye-movement analyses in an adaptive learning environment. In: L. Lin and R.K. Atkinson, eds. Educational Technologies: Challenges, Applications and Learning Outcomes. Nova Science Publishers, Inc., Education in a Competitive and
Globalizing World, pp.115–142. URL https://www.researchgate.net/publication/
316062339.
[188] Slater, S., Ocumpaugh, J., Baker, R., Li, J. and Labrum, M., 2018. Identifying changes
in math identity through adaptive learning systems use. In: M.M.T. Rodrigo,
J.C. Yang, L.H. Wong and M. Chang, eds. ICCE 2018 - 26th International Conference on Computers in Education, Main Conference Proceedings. Asia-Pacific Society
for Computers in Education, pp.71–76. URL https://learninganalytics.upenn.edu/
ryanbaker/i_paper_93.pdf.
[189] Smith, K., 2018. Perceptions of preservice teachers about adaptive learning programs in K-8 mathematics education. Contemporary Educational Technology, 9(2),
pp.111–130. URL https://doi.org/10.30935/cet.414780.
[190] Sosnovsky, S. and Chacon, I.A., 2014. Semantic gap detection in metadata of adaptive learning environments. In: D.G. Sampson, M.J. Spector, N.S. Chen, R. Huang
and Kinshuk, eds. Proceedings - IEEE 14th International Conference on Advanced
Learning Technologies, ICALT 2014. Institute of Electrical and Electronics Engineers Inc., pp.548–552. URL https://doi.org/10.1109/ICALT.2014.161.
[191] Stewart, C. and Wolodko, B., 2016. University Educator Mindsets: How Might
Adult Constructive-Developmental Theory Support Design of Adaptive Learning?
Mind, Brain, and Education, 10(4), pp.247–255. URL https://doi.org/10.1111/mbe.
12126.
[192] Su, C.H., 2017. Designing and developing a novel hybrid adaptive learning path
recommendation system (ALPRS) for gamification mathematics geometry course.
Eurasia Journal of Mathematics, Science and Technology Education, 13(6), pp.2275–2298. URL https://doi.org/10.12973/EURASIA.2017.01225A.
[193] Sun, Q., Norman, T.J. and Abdourazakou, Y., 2018. Perceived value of interactive digital textbook and adaptive learning: Implications on student learning effectiveness. Journal of Education for Business, 93(7), pp.322–330. URL
https://doi.org/10.1080/08832323.2018.1493422.
[194] Surahman, E., Kuswandi, D., Wedi, A., Degeng, I.N.S., Setyanti, D.A. and Thaariq,
Z.Z.A., 2019. Adaptive learning analytics management system (Alams): An innovative online learning approach. International Journal of Innovation, Creativity
and Change, 5(4), pp.413–430.
[195] Szijarto, B. and Cousins, J.B., 2019. Making Space for Adaptive Learning.
American Journal of Evaluation, 40(2), pp.160–176. URL https://doi.org/10.1177/
1098214018781506.
[196] Tackett, S., Raymond, M., Desai, R., Haist, S.A., Morales, A., Gaglani, S. and
Clyman, S.G., 2018. Crowdsourcing for assessment items to support adaptive learning. Medical Teacher, 40(8), pp.838–841. URL https://doi.org/10.1080/
0142159X.2018.1490704.
[197] Tamo-Vargas, G., Quispe-Pari, E., Bedregal-Alpaca, N., Guevara, K., DelgadoBarra, L. and Laura-Ochoa, L., 2023. Design and development of a Moodle
Plugin for the adaptation of the teaching-learning process through graded
grading constraints; [Diseno y desarrollo de un Plugin en Moodle para la ˜
adaptacion de proceso ense ´ nanza-aprendizaje a trav ˜ es de restricciones de ´
calificacion escalonada]. ´ RISTI - Revista Iberica de Sistemas e Tecnologias de
Informacao. Associacao Iberica de Sistemas e Tecnologias de Informacao,
vol. 2023, pp.338–351. URL https://pure.unsa.edu.pe/en/publications/dise%
C3%B1o-y-desarrollo-de-un-plugin-en-moodle-para-la-adaptaci%C3%B3n-de-/fingerprints/.
[198] Tashiro, J.S., Hung, P.C.K., Martin, M.V., Brown, A.L. and Hurst, F.M., 2016.
Personalised-adaptive learning - An operational framework for developing
competency-based curricula in computer information technology. International
Journal of Innovation and Learning, 19(4), pp.412–430. URL https://doi.org/10.
1504/IJIL.2016.076793.
[199] Tonkonohyy, V.M., 2013. Theory and practice of implementation of computer technologies of teaching and knowledge control of special technical disciplines using
adaptive technologies. (0214U007002). Odessa National Polytechnic University.
URL https://nrat.ukrintei.ua/searchdoc/0214U007002.
[200] Torrano, F. and Gonzalez-Torres, M.C., 2016. Initial study of the psychometric ´
properties of the motivational scales of the PALS (Patterns of Adaptive Learning
Scales) focusing on the student [Estudio inicial de las propiedades psicometricas ´
de las escalas motivacionales del PALS (Patterns of Adaptive Learning Scales)
centradas en el alumno]. Estudios Pedagogicos, 42(3), pp.391–412. URL https:
//doi.org/10.4067/s0718-07052016000400021.
[201] Tortorella, R.A.W. and Graf, S., 2017. Considering learning styles and contextawareness for mobile adaptive learning. Education and Information Technologies,
22(1), pp.297–315. URL https://doi.org/10.1007/s10639-015-9445-x.
[202] Tsai, M.H. and Huang, C.H., 2019. Application of data mining theory to investigate
factors impacting high school students’ adaptive learning in Taiwan. Contemporary Educational Research Quarterly, 27(2), pp.39–76. URL https://doi.org/10.6151/
CERQ.201906_27(2).0002.
[203] Ueno, H., Kato, T., Fukamachi, K., Tateno, H., Yamakawa, H. and Komatsugawa,
H., 2018. The Case Study of a Flipped Classroom Using an Adaptive Learning System. In: M.M.T. Rodrigo, S. Amalathas, A.D. Coronel, J.C. Yang, Y. Song, J. Ding,
M. Chang and L.H. Wong, eds. ICCE 2018 - 26th International Conference on Computers in Education, Work-in-Progress Poster Proceedings. Asia-Pacific Society for
Computers in Education, pp.4–6. URL http://tinyurl.com/3cd67kxt.
[204] Ueno, H., Kato, T., Yoshida, F., Tsukada, N., Tateno, H., Fukamachi, K., Yamakawa,
H. and Komatsugawa, H., 2018. A model of flipped classroom using an adaptive
learning system. In: J.C. Yang, C. Yin, W. Chen, A. Mohd Ayub, A. Mitrovic, J. Ding,
S. Amalathas and S.L. Wong, eds. ICCE 2017 - 25th International Conference on
Computers in Education: Technology and Innovation: Computer-Based Educational
Systems for the 21st Century, Work In Progress Posters Proceedings. Asia-Pacific Society for Computers in Education, pp.1–3.
[205] Verkhovna Rada of Ukraine, 2014. Law of Ukraine On Higher Education. URL
https://zakon.rada.gov.ua/laws/show/1556-18?lang=en#Text.
[206] Verkhovna Rada of Ukraine, 2018. Law of Ukraine On Education. URL https:
//zakon.rada.gov.ua/laws/show/2145-19?lang=en#Text.
[207] Vitez, A., 2022. Course module instances report. URL https://moodle.org/plugins/
report_coursemodstats.
[208] Vo, K. and Dutkiewicz, E., 2019. Optimal length-constrained segmentation and
subject-adaptive learning for real-time arrhythmia detection. Proceedings - 2018
IEEE/ACM International Conference on Connected Health: Applications, Systems and
Engineering Technologies, CHASE 2018. Institute of Electrical and Electronics Engineers Inc., vol. 2019-January, pp.112–119. URL https://doi.org/10.1145/3278576.
3284385.
[209] Vu Minh, C., 2005. Constructivist learning: an operational approach for designing
adaptive learning environments supporting cognitive flexibility. PhD thesis. Universite Catholique de Louvain. URL http://hdl.handle.net/2078.1/5145. ´
[210] Vyshnevska, V.M., 2007. The system of adaptive studies is on principles of fuzzy
logic. Dissertation is on the receipt of scientific degree of candidate of engineerings
sciences after speciality 05.13.06 – Control the system and progressive information
technologies is automated. Odessa national polytechnic university, Odessa. URL
https://nrat.ukrintei.ua/searchdoc/0407U004559.
[211] Vasquez-Berm ´ udez, M., Aguirre-Munizaga, M. and Hidalgo-Larrea, J., 2023. ´
Analysis of CoI Presence Indicators in a Moodle Forum Using Unsupervised
Learning Techniques. In: R. Valencia-Garc´ıa, M. Bucaram-Leverone, J. Del
Cioppo-Morstadt, N. Vera-Lucio and P.H. Centanaro-Quiroz, eds. Communications in Computer and Information Science. Springer Science and Business Media Deutschland GmbH, vol. 1873 CCIS, pp.27 – 38. URL https://doi.org/10.1007/
978-3-031-45682-4_3.
[212] Walkington, C. and Sherman, M., 2012. Using adaptive learning technologies to
personalize instruction: The impact of interest-based scenarios on performance
in Algebra. 10th International Conference of the Learning Sciences: The Future of
Learning, ICLS 2012 - Proceedings. vol. 1, pp.80–87. URL https://doi.org/10.22318/
icls2012.1.80.
[213] Walkington, C.A., 2013. Using adaptive learning technologies to personalize instruction to student interests: The impact of relevant contexts on performance
and learning outcomes. Journal of Educational Psychology, 105(4), pp.932–945.
URL https://doi.org/10.1037/a0031882.
[214] Wang, S., Feng, M., Bienkowski, M., Christensen, C. and Cui, W., 2019. Learning
from an adaptive learning system: Student profiling among middle school students. In: H. Lane, S. Zvacek and J. Uhomoibhi, eds. CSEDU 2019 - Proceedings of the 11th International Conference on Computer Supported Education. SciTePress,
vol. 1, pp.78–84. URL https://doi.org/10.5220/0007729700780084.
[215] Wang, Y.H. and Liao, H.C., 2011. Adaptive learning for ESL based on computation.
British Journal of Educational Technology, 42(1), pp.66–87. URL https://doi.org/10.
1111/j.1467-8535.2009.00981.x.
[216] Welsh, S. and Uys, P., 2019. Dreaming of electric sheep: CSU’s vision for analyticsdriven adaptive learning and teaching. ASCILITE 2015 - Australasian Society
for Computers in Learning and Tertiary Education, Conference Proceedings. Australasian Society for Computers in Learning in Tertiary Education (ASCILITE),
pp.593–598. URL https://www.researchgate.net/publication/290411880.
[217] Werlen, E. and Bergamin, P., 2018. Self-evaluation of open answers as a basis for
adaptive learning systems. In: D.G. Sampson, P. Isaias, D. Ifenthaler and L. Rodrigues, eds. Proceedings of the 15th International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2018. IADIS Press, pp.335–340. URL
https://www.researchgate.net/publication/326957895.
[218] Yang, T.C., Hwang, G.J. and Yang, S.J.H., 2013. Development of an adaptive
learning system with multiple perspectives based on students’ learning styles
and cognitive styles. Educational Technology and Society, 16(4), pp.185–200. URL
https://www.jstor.org/stable/jeductechsoci.16.4.185.
[219] Yang, Y.T.C., Gamble, J.H., Hung, Y.W. and Lin, T.Y., 2014. An online adaptive learning environment for critical-thinking-infused English literacy instruction. British Journal of Educational Technology, 45(4), pp.723–747. URL https:
//doi.org/10.1111/bjet.12080.
[220] Yeti¸sir, M.˙
I. and Ceylan, E., 2015. The adaptation of students’ adaptive learning
engagement in science scale into Turkish [Fen O¨ grenimine y ˘ onelim ¨ Ol¸ce ¨ ginin ˘ turk¸ce’ ye uyarlanması]. ¨ Elementary Education Online, 14(2), pp.657–670. URL
https://doi.org/10.17051/io.2015.49510.
[221] Yuan, R.Q., Hsieh, S.W., Chew, S.W. and Chen, N.S., 2016. The Effects of
Gesture-Based Technology on Memory Training in Adaptive Learning Environment. In: L. Chen, C.C. Tsai, H.H. Yang, H.H. Yang, X. Yu, Q. Liu, S. Wang and
J. Cheng, eds. Proceedings - 2015 International Conference of Educational Innovation
Through Technology, EITT 2015. Institute of Electrical and Electronics Engineers
Inc., pp.190–193. URL https://doi.org/10.1109/EITT.2015.47.
[222] Yurchenko, K.M., 2012. Adaptive technology of educating and determination for
professional preparedness level of operatively-rescue service specialists. Thesis for
Ph.D degree in the specialty 05.13.06 – Information technologies. Cherkasy
State Technological University, Cherkasy. URL https://nrat.ukrintei.ua/searchdoc/
0412U004271.
[223] Zhang, J.C., 2016. Adaptive learning environment system based on multi-event
driven technology. International Journal of Emerging Technologies in Learning,
11(11), pp.37–42. URL https://doi.org/10.3991/ijet.v11i11.6250.
[224] Zhao, L. and Wang, H., 2019. Research on adaptive learning system based on three
core modules. Proceedings - 10th International Conference on Information Technology in Medicine and Education, ITME 2019. Institute of Electrical and Electronics
Engineers Inc., pp.447–452. URL https://doi.org/10.1109/ITME.2019.00106.
[225] Zhou, Z., Zhang, Q., Lu, G., Wang, H., Zhang, W. and Yu, Y., 2019. Adashift: Decorrelation and convergence of adaptive learning rate methods. 7th International
Conference on Learning Representations, ICLR 2019. International Conference on
Learning Representations, ICLR. URL https://doi.org/10.48550/arXiv.1810.00143.
[226] Ziimpe, M., 2011. Determination, adaptive learning and monetary policy rules in the new canonical model: A primer [Determination, apprentissage adaptatif et ´
regles de politique mon ` etaire dans le nouveau mod ´ ele canonique: Un guide de `
lecture]. Revue d’Economie Politique, 121(3), pp.307–345. URL https://doi.org/10.
3917/redp.213.0307.
[227] Zulfiani, Z., Suwarna, I.P. and Miranto, S., 2018. Science education adaptive learning system as a computer-based science learning with learning style variations.
Journal of Baltic Science Education, 17(4), pp.711–727. URL https://doi.org/10.
33225/jbse/18.17.711.