Evaluating system design features
International Journal of Human-Computer Studies
Predictive Statistical Models for User Modeling
User Modeling and User-Adapted Interaction
ELM-ART: An Intelligent Tutoring System on World Wide Web
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Curriculum Sequencing in a Web-Based Tutor
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
AHA! The adaptive hypermedia architecture
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
A person-artefact-task (PAT) model of flow antecedents in computer-mediated environments
International Journal of Human-Computer Studies - Special issue on HCI and MIS
Developing creativity, motivation, and self-actualization with learning systems
International Journal of Human-Computer Studies - Special issue: Computer support for creativity
Understanding e-learning continuance intention: An extension of the Technology Acceptance Model
International Journal of Human-Computer Studies
What is user engagement? A conceptual framework for defining user engagement with technology
Journal of the American Society for Information Science and Technology
The impact of multimedia effect on science learning: Evidence from eye movements
Computers & Education
Usability, quality, value and e-learning continuance decisions
Computers & Education
To Flow and Not to Freeze: Applying Flow Experience to Mobile Learning
IEEE Transactions on Learning Technologies
e-Learning continuance intention: Moderating effects of user e-learning experience
Computers & Education
Risky business or sharing the load? - Social flow in collaborative mobile learning
Computers & Education
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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With the growing demand in e-learning system, traditional e-learning systems have dramatically evolved to provide more adaptive ways of learning, in terms of learning objectives, courses, individual learning processes, and so on. This paper reports on differences in learning experience from the learner's perspectives when using an adaptive e-learning system, where the learner's knowledge or skill level is used to configure the learning path. Central to this study is the evaluation of a dynamic content sequencing system (DCSS), with empirical outcomes being interpreted using Csikszentmihalyi's flow theory (i.e., Flow, Boredom, and Anxiety). A total of 80 participants carried out a one-way between-subject study controlled by the type of e-learning system (i.e., the DCSS vs. the non-DCSS). The results indicated that the lower or medium achievers gained certain benefits from the DCSS, whilst the high achievers in learning performance might suffer from boredom when using the DCSS. These contrasting findings can be suggested as a pragmatic design guideline for developing more engaging computer-based learning systems for unsupervised learning situations.