Journal of Educational Multimedia and Hypermedia Volume 24, Number 4, ISSN 1055-8896 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners’ cognitive development and ability. The results showed that students made significant improvements after learning with the tutor control learning system. Based on the results of adaptive assessment, the system provided just-in-time personalized instructional materials that better aligned with students’ knowledge. Students spent less time reading the instructional materials, which increased the learning efficiency. The findings are discussed in terms of tutor versus learner control, and recommendations are provided for future design and research in the area of multimedia learning system.
Chen, C.H. & Chang, S.W. (2015). Effectiveness of adaptive assessment versus learner control in a multimedia learning system. Journal of Educational Multimedia and Hypermedia, 24(4), 321-341. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved March 24, 2019 from https://www.learntechlib.org/primary/p/149394/.
© 2015 Association for the Advancement of Computing in Education (AACE)
- Brusilovsky, P. (1994). The construction and application of student models in intelligent tutoring systems. Journal of Computer and Systems Sciences International, 32, 70-89.
- Brusilovsky, P. (1999). Adaptive and intelligent technologies for web-based education. Special Issue on Intelligent Systems and Teleteaching, Künstliche Intelligenz, 19-25.
- Brusilovsky, P. (2001). Adaptive hypermedia. User Modeling and User-adapted Interaction, 11(2/3), 87-110. Brusilovsky, P., eklund, J., & Schwarz, E. (1998). Web-based education for all: a tool for development adaptive courseware. Computer Networking 30, Effectiveness of Adaptive Assessment Versus Learner Control 339
- Chen, S.-L. (2009). Developing a model for adaptive learning of foreign languages-Research on the german conversation. Soochow Journal of Foreign Languages and Literatures, 29, 81-104.
- Chu, C.-P., Chang, Y.-C., & Tsai, C.-C. (2011). PC2PSO: Personalized e-course composition based on particle swarm optimization. Applied Intelligence, 34, 141-154.
- Koper, R. (2005). Increasing learner retention in a simulated learning network using indirect social interaction. Journal of Artificial Societies and Social Simulation, 8(2), 1-19.
- Lo, J.-J., & Shu, P.-C. (2005). Identification of learning styles online by observing learners’ browsing behaviour through a neural network. British Journal of Educational Technology, 36, 43-55.
- Merrell, C., & Tymms, P. (2007). Identifying Reading Problems with Computeradaptive assessments. Journal of Computer Assisted Learning, 23(1), 2735.
- Myers, LB. (1962). Manual: The Myers-Briggs Type Indicator. Princeton, nJ: educational Testing Services. Papanikolaou, K.A., grigoriadoua, M. , Magoulas, george D., & Kornilakis, harry. (2002). Towards new forms of knowledge communication:the adaptive dimension of a web-based learning environment. Computers& Education, 39, 333-360.
- Phobun, P., & Vicheanpanya, J. (2010). Adaptive intelligent tutoring systems for e-learning systems. Procedia-Social and Behavioral Sciences, 2, 40644069.
- Zheng, R. (2010). Effects of situated learning on studentsʼ knowledge acquisition: an individual differences perspective. Journal of Educational Comput DASHDASH
These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact email@example.com.