Research Article
User Interface Design of Student’s Metacognitive Classification for Adaptive Metacognitive Hypermedia Learning Environment System (HLE)
@INPROCEEDINGS{10.4108/eai.18-11-2023.2342547, author={Qonitatul Hasanah and Intan Sulistyaningrum Sakkinah and Raditya Arief Pratama}, title={User Interface Design of Student’s Metacognitive Classification for Adaptive Metacognitive Hypermedia Learning Environment System (HLE)}, proceedings={Proceedings of the 4th International Conference on Social Science, Humanity and Public Health, ICoSHIP 2023, 18-19 November 2023, Surabaya, East Java, Indonesia}, publisher={EAI}, proceedings_a={ICOSHIP}, year={2024}, month={1}, keywords={adaptive hypermedia learning environment user interface design student classification}, doi={10.4108/eai.18-11-2023.2342547} }
- Qonitatul Hasanah
Intan Sulistyaningrum Sakkinah
Raditya Arief Pratama
Year: 2024
User Interface Design of Student’s Metacognitive Classification for Adaptive Metacognitive Hypermedia Learning Environment System (HLE)
ICOSHIP
EAI
DOI: 10.4108/eai.18-11-2023.2342547
Abstract
Hypermedia Learning Environment (HLE) is a learning media that uses the concept of multimedia learning and organizes it as an information structure that resembles a network. Adaptive Metacognitive HLE is an HLE that can adapt to the user's persona, i.e., metacognitive abilities. This research designed the HLE system interface for classifying student metacognitive abilities with Unified Modelling Language (UML). The metacognitive abilities of students were integrated with the adaptive HLE, enabling them to gain a heightened awareness of their learning processes, comprehend their strengths and weaknesses, and manage their learning more effectively. This can help improve learning performance, promote problem-solving, and facilitate deeper and more abstract understanding. The result of this research is a system design with Data Flow Diagrams and User Interface design. Further research can evaluate the user experience associated with the implementation of a classification system within the HLE, providing valuable insights into its practicality and effectiveness.