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pro vyhledávání: '"Thushari Atapattu"'
Leveraging Inference: A Regression-Based Learner Performance Prediction System for Knowledge Tracing
Publikováno v:
IEEE Access, Vol 11, Pp 123458-123475 (2023)
Learner modelling and performance prediction have seen numerous advances in the last decade which include Neural Network (NN) based approaches like Deep Knowledge Tracing (DKT), Factorisation machines for estimation and automatic detection of skill t
Externí odkaz:
https://doaj.org/article/f785f72a2b794c39aff07c3756689842
Publikováno v:
PeerJ Computer Science, Vol 5, p e235 (2019)
As scientific publication rates increase, knowledge acquisition and the research development process have become more complex and time-consuming. Literature-Based Discovery (LBD), supporting automated knowledge discovery, helps facilitate this proces
Externí odkaz:
https://doaj.org/article/75962195bf564b439aec889af08cb740
Autor:
Thushari Atapattu, Menasha Thilakaratne, Lavendini Sivaneasharajah, Katrina Falkner, Rangana Jayashanka
Publikováno v:
IEEE Transactions on Learning Technologies. 13:878-888
The substantial growth of online learning, and in particular, through massively open online courses (MOOCs), supports research into nontraditional learning contexts. Learners’ confusion is one of the identified aspects which impact the overall lear
Publikováno v:
JCDL
Literature-Based Discovery (LBD) which is a sub-discipline of text mining, aims to detect meaningful implicit knowledge linkages in digital libraries that have the potential in generating novel research hypotheses. The input can be considered as one
Publikováno v:
JCDL
Literature-Based Discovery (LBD) refers to the process of detecting implicit, novel knowledge linkages hidden in scientific digital libraries and its contribution in accelerating research innovations is widely recognised. Despite significant advances
Publikováno v:
ESEC/SIGSOFT FSE
Good software documentation encourages good software engineering, but the meaning of "good" documentation is vaguely defined in the software engineering literature. To clarify this ambiguity, we draw on work from the data and information quality comm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f831f9fb0d6be0d61a06d616028ca85b
http://arxiv.org/abs/2007.10744
http://arxiv.org/abs/2007.10744
Publikováno v:
WOAH
Cyberbullying is a prevalent social problem that inflicts detrimental consequences to the health and safety of victims such as psychological distress, anti-social behaviour, and suicide. The automation of cyberbullying detection is a recent but widel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::766d8dc0575c50d639bbe495cbe04cd4
Publikováno v:
SemEval@COLING
This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks – offensive language identification (subtask A), offen
Publikováno v:
Computers & Education. 115:96-113
Current instructional methods widely support verbal learning through linear and sequential teaching materials, focusing on isolated pieces of information. However, an important aspect of learning design is to facilitate students in identifying relati
Autor:
Thushari Atapattu, Katrina Falkner
Publikováno v:
Journal of Learning Analytics; Vol 5 No 3 (2018): Selected and Extended Papers from the Eighth International Conference on Learning Analytics & Knowledge; 182–197
Lecture videos are amongst the most widely used instructional methods in present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, students’ engagement behaviour with videos directly impac