Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Ani Grubišić"'
Autor:
Ani Grubišić, Slavomir Stankov, Branko Žitko, Ines Šarić-Grgić, Angelina Gašpar, Emil Brajković, Daniel Vasić
Publikováno v:
Journal of Universal Computer Science, Vol 29, Iss 8, Pp 866-891 (2023)
This paper describes and evaluates the performance of a semi-automatic authoring tool (SAAT) for knowledge extraction in the AC&NL Tutor, highlighting its strengths and weaknesses. We assessed the accuracy of automatic annotation tasks (Part-of-Speec
Externí odkaz:
https://doaj.org/article/ce61c2451c934d01a425d45670b071e4
Publikováno v:
Journal of Technology and Science Education, Vol 10, Iss 1, Pp 60-71 (2020)
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper,
Externí odkaz:
https://doaj.org/article/adb2484486a7429abd069b98e722cc0b
Autor:
Ani Grubišić, Branko Žitko, Slavomir Stankov, Ines Šarić-Grgić, Angelina Gašpar, Suzana Tomaš, Emil Brajković, Tomislav Volarić, Daniel Vasić, Arta Dodaj
Publikováno v:
Je-LKS: Journal of E-Learning and Knowledge Society, Vol 16, Iss 3 (2020)
E-Learning environment implies self-motivation and perseverance in study and completion of learning tasks. However, the more autonomy students have in managing their e-Learning, the harder they cope with distractions and remaining focused and engaged
Externí odkaz:
https://doaj.org/article/9f53504bbfbc4eca9b9ae1b08de493b9
Akademický článek
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Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031328824
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dca4e36363f569691bb18c7fd6188ad
https://doi.org/10.1007/978-3-031-32883-1_19
https://doi.org/10.1007/978-3-031-32883-1_19
Various approaches to text simplification have been proposed in an attempt to increase text readability. The rephrasing of syntactically and semantically complex structures is still challenging. A pedagogically motivated simplified version of the sam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c7fccbeab1305a9b19309d967a6dfa1
https://www.bib.irb.hr/1156020
https://www.bib.irb.hr/1156020
Publikováno v:
Journal of Technology and Science Education, Vol 10, Iss 1, Pp 60-71 (2020)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper,
Autor:
Ivan Peraić, Daniel Vasić, Angelina Gašpar, Ani Grubišić, Matea Markić-Vučić, Slavomir Stankov, Suzana Tomaš, Branko Žitko, Ines Šarić-Grgić
Publikováno v:
Adaptive Instructional Systems. Design and Evaluation ISBN: 9783030778569
HCI (31)
HCI (31)
In this article we present an knowledge extraction approach that can be used in systems that implement teaching in a fully automated manner. These systems are called Intelligent Tutoring Systems (ITS) and are conceived around the idea of one-to-one t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ef8d2cc8fa4bbf258283b3c4b706295
https://doi.org/10.1007/978-3-030-77857-6_23
https://doi.org/10.1007/978-3-030-77857-6_23
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd2a74e5de9c6ffa25733c4155bd2f86
https://www.bib.irb.hr/1051197
https://www.bib.irb.hr/1051197
Autor:
Ines Šarić-Grgić, Daniel Vasić, Angelina Gašpar, Branko Žitko, Slavomir Stankov, Suzana Tomaš, Ani Grubišić
Publikováno v:
Adaptive Instructional Systems ISBN: 9783030507879
HCI (34)
HCI (34)
The reasoning process about the level of student’s knowledge can be challenging even for experienced human tutors. The Bayesian networks are a formalism for reasoning under uncertainty, which has been successfully used for various artificial intell
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4755deced0dc6d34147ca172b77584a9
https://www.bib.irb.hr/1087586
https://www.bib.irb.hr/1087586