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Danial Hooshyar
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2020 – today
- 2024
- [j28]Danial Hooshyar
, Yeongwook Yang
Problems With SHAP and LIME in Interpretable AI for Education: A Comparative Study of Post-Hoc Explanations and Neural-Symbolic Rule Extraction. IEEE Access 12: 137472-137490 (2024) - [j27]Danial Hooshyar
The effectiveness of personalized technology-enhanced learning in higher education: A meta-analysis with association rule mining. Comput. Educ. 223: 105169 (2024) - [j26]Danial Hooshyar
Temporal learner modelling through integration of neural and symbolic architectures. Educ. Inf. Technol. 29(1): 1119-1146 (2024) - [j25]Danial Hooshyar
ImageLM: Interpretable image-based learner modelling for classifying learners' computational thinking. Expert Syst. Appl. 238(Part E): 122283 (2024) - [j24]Danial Hooshyar
Augmenting Deep Neural Networks with Symbolic Educational Knowledge: Towards Trustworthy and Interpretable AI for Education. Mach. Learn. Knowl. Extr. 6(1): 593-618 (2024) - 2023
- [j23]Danial Hooshyar
Modeling Learners to Early Predict Their Performance in Educational Computer Games. IEEE Access 11: 20399-20417 (2023) - [i1]Danial Hooshyar, Roger Azevedo, Yeongwook Yang:
Augmenting deep neural networks with symbolic knowledge: Towards trustworthy and interpretable AI for education. CoRR abs/2311.00393 (2023) - 2022
- [j22]Danial Hooshyar
Effects of technology-enhanced learning approaches on learners with different prior learning attitudes and knowledge in computational thinking. Comput. Appl. Eng. Educ. 30(1): 64-76 (2022) - [j21]Danial Hooshyar, Yueh-Min Huang, YeongWook Yang:
GameDKT: Deep knowledge tracing in educational games. Expert Syst. Appl. 196: 116670 (2022) - [c10]Yu-Cheng Chien, Pei-Yu Cheng, Lin-Tao Csui, YeongWook Yang, Danial Hooshyar, Yueh-Min Huang:
Exploring the Relationship Between Learning Achievement and Discussion Records in Remote Maker Activities. ICITL 2022: 43-51 - 2021
- [j20]Danial Hooshyar, Liina Malva
An adaptive educational computer game: Effects on students' knowledge and learning attitude in computational thinking. Comput. Hum. Behav. 114: 106575 (2021) - [c9]Hsin-Yu Lee, Yu-Cheng Chien, Pei-Yu Chang, Danial Hooshyar, Yueh-Min Huang:
Use Object-Detection to Identify Materials and Tools for STEAM Hands-on Activity. ICITL 2021: 39-48 - 2020
- [j19]Danial Hooshyar
Clustering Algorithms in an Educational Context: An Automatic Comparative Approach. IEEE Access 8: 146994-147014 (2020) - [j18]Danial Hooshyar, Margus Pedaste, Katrin Saks
Open learner models in supporting self-regulated learning in higher education: A systematic literature review. Comput. Educ. 154: 103878 (2020) - [j17]Danial Hooshyar, Margus Pedaste
Mining Educational Data to Predict Students' Performance through Procrastination Behavior. Entropy 22(1): 12 (2020) - [j16]Seolhwa Lee, Dongyub Lee, Danial Hooshyar, Jaechoon Jo
Integrating breakdown detection into dialogue systems to improve knowledge management: encoding temporal utterances with memory attention. Inf. Technol. Manag. 21(1): 51-59 (2020) - [j15]YeongWook Yang
A group preference-based item similarity model: comparison of clustering techniques in ambient and context-aware recommender systems. J. Ambient Intell. Humaniz. Comput. 11(4): 1441-1449 (2020) - [j14]YeongWook Yang
Predicting course achievement of university students based on their procrastination behaviour on Moodle. Soft Comput. 24(24): 18777-18793 (2020) - [c8]Nour El Mawas, Danial Hooshyar, YeongWook Yang:
Effects of Adaptive Educational Games on Adults' Computational Thinking. CSEDU (Selected Papers) 2020: 162-176 - [c7]Nour El Mawas, Danial Hooshyar, YeongWook Yang:
Investigating the Learning Impact of Autothinking Educational Game on Adults: A Case Study of France. CSEDU (2) 2020: 188-196 - [c6]Liina Malva
Engaging Estonian primary school children in computational thinking through adaptive educational games: A qualitative study. ICALT 2020: 188-190 - [c5]Emanuele Bardone, Danial Hooshyar, Margus Pedaste:
Theorising the Open Learner Model as an educational tool: An Open Challenge. ICALT 2020: 275-276 - [c4]Danial Hooshyar, Emanuele Bardone, Nour El Mawas, YeongWook Yang
Transparent Player Model: Adaptive Visualization of Learner Model in Educational Games. ICITL 2020: 349-357
2010 – 2019
- 2019
- [j13]Danial Hooshyar
A systematic review of data-driven approaches in player modeling of educational games. Artif. Intell. Rev. 52(3): 1997-2017 (2019) - [j12]Danial Hooshyar, Külli Kori
The potential of open learner models to promote active thinking by enhancing self-regulated learning in online higher education learning environments. Br. J. Educ. Technol. 50(5): 2365-2386 (2019) - [j11]Danial Hooshyar
Long-term effects of adaptive customization support on elderly people. Cogn. Technol. Work. 21(3): 371-382 (2019) - [j10]YeongWook Yang
GPS: Factorized group preference-based similarity models for sparse sequential recommendation. Inf. Sci. 481: 394-411 (2019) - [j9]Hyesung Ji, Danial Hooshyar
A semantic-based video scene segmentation using a deep neural network. J. Inf. Sci. 45(6) (2019) - [j8]Heuiseok Lim, Danial Hooshyar
SmartSenior: Automatic Content Personalization Through Semi-supervised Learning. Wirel. Pers. Commun. 105(2): 461-473 (2019) - [c3]Danial Hooshyar, Heuiseok Lim, Margus Pedaste, Kisu Yang, Moein Fathi, YeongWook Yang
AutoThinking: An Adaptive Computational Thinking Game. ICITL 2019: 381-391 - 2018
- [j7]SeolHwa Lee, Danial Hooshyar
Mining biometric data to predict programmer expertise and task difficulty. Clust. Comput. 21(1): 1097-1107 (2018) - [j6]Danial Hooshyar
Data-Driven Approaches to Game Player Modeling: A Systematic Literature Review. ACM Comput. Surv. 50(6): 90:1-90:19 (2018) - [j5]Danial Hooshyar
A data-driven procedural-content-generation approach for educational games. J. Comput. Assist. Learn. 34(6): 731-739 (2018) - [j4]Youdong Yun, Danial Hooshyar
Developing a hybrid collaborative filtering recommendation system with opinion mining on purchase review. J. Inf. Sci. 44(3): 331-344 (2018) - 2016
- [j3]Danial Hooshyar
Applying an online game-based formative assessment in a flowchart-based intelligent tutoring system for improving problem-solving skills. Comput. Educ. 94: 18-36 (2016) - [c2]SeolHwa Lee, Andrew Matteson, Danial Hooshyar
Comparing Programming Language Comprehension between Novice and Expert Programmers Using EEG Analysis. BIBE 2016: 350-355 - 2015
- [j2]Danial Hooshyar
Flowchart-based programming environments for improving comprehension and problem-solving skill of novice programmers: a survey. Int. J. Adv. Intell. Paradigms 7(1): 24-56 (2015) - [j1]Danial Hooshyar
A flowchart-based intelligent tutoring system for improving problem-solving skills of novice programmers. J. Comput. Assist. Learn. 31(4): 345-361 (2015) - 2014
- [c1]Danial Hooshyar
A framework for automatic text-to-flowchart conversion: A novel teaching aid for novice programmers. IC3INA 2014: 7-12
Coauthor Index
aka: Yeongwook Yang
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last updated on 2024-11-07 20:33 CET by the dblp team
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