Abstract
Multimedia content comprises the graphics, audio & video clips, animation and text to present learning materials in a style, which improves learner expectation in eLearning paradigm. Electronic learning gained the popularity due to its immense coverage of students and subjects all over the world. The aim of this study is enhancements using agent-based framework through multimedia data in eLearning paradigm. Analysis of multimedia contents and eLearning data are helpful for the course designers, teachers, and administrators of eLearning environments to hunt for undetected patterns and underlying data in learning processes. This research improves the learning curves for the students. It also needs to improve the overall processes in eLearning paradigm. Information and Communication Technologies supported education, and virtual classrooms environments are mandatory. In eLearning data is evolving day by day that includes the semi-structured data, unstructured data, and structured data which is also collectively marked as multimedia big data. Multimedia data has the potential to mining for the analytics and learning. The learning outcomes for the students are very important to find the facts that what impacts the input data on the student. There are 1108 students posted questions in online Learning Management System (LMS) and instructors reply these queries. Sensor data is also gathered by the mobile GPS to find the student location. The system has analyzed the relevance of the replied answers. The student satisfaction is achieved by providing the multimedia-based student-teacher interaction. This can lead to synchronous communication and multimedia content conversation in eLearning paradigm. Machine learning techniques are applied to that data to discover the patterns and behavioral trends. It can also be used in the eLearning environments for the teacher to assist and enhance the pedagogical skills and for student’s learning curve enhancements.
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References
Chen H, Chiang RH, Storey VC (2012) Business Intelligence and analytics: from big data to big impact. MIS Q 36(4):1165–1188
Dominici G, Palumbo F (2013) How to build an e-learning product: factors for student/customer satisfaction. Bus Horiz 56(1):87–96
Farhan M et al (2012) Automated reply to students' queries in E-Learning environment using Web-BOT. In Artificial Intelligence (MICAI), 2012 11th Mexican International Conference on. IEEE
Jabbar S et al (2016) Trust model at service layer of cloud computing for educational institutes. J Supercomput 72(1):58–83
Jeong H-Y, Yeo S-S (2014) The quality model for e-learning system with multimedia contents: a pairwise comparison approach. Multimedia Tools and Applications 73(2):887–900
Jones K, Geraniou E, Tiropanis T (2013) Patterns of collaboration: towards learning mathematics in the era of the semantic web. In Visual mathematics and cyberlearning. Springer. p 1–21
Jung I, Sasaki T, Latchem C (2016) A framework for assessing fitness for purpose in open educational resources. International Journal of Educational Technology in Higher Education 13(1):1
Kaur P, Sharma P, Vohra N (2015) An ontology based E-learning system. International Journal of Grid and Distributed Computing 8(5):273–278
Khalid S et al (2015) Accurate and efficient shape matching approach using vocabularies of multi-feature space representations. J Real-Time Image Process. doi:10.1007/s11554-015-0545-z
Lange C (2013) Ontologies and languages for representing mathematical knowledge on the semantic web. Semantic Web 4(2):119–158
Malik KR et al (2015) Big-data: transformation from heterogeneous data to semantically-enriched simplified data. Multimedia Tools and Applications 75(20):1–21
Mishra M, Mishra VK, Sharma H (2013) Question classification using semantic, syntactic and lexical features. International Journal of Web & Semantic Technology 4(3):39
Munwar Iqbal M, Farhan M, Saleem Y, Aslam M (2014) Automated web-bot implementation using machine learning techniques in eLearning paradigm. J Appl Environ Biol Sci 4(7S):9
Naseer MK, Jabbar S, Zafar I (2014) A novel trust model for selection of Cloud Service Provider. in Computer Applications & Research (WSCAR), 2014 World Symposium on. IEEE
Nassirtoussi AK et al (2014) Text mining for market prediction: a systematic review. Expert Syst Appl 41(16):7653–7670
Papanikolaou Y et al (2014) Ensemble approaches for large-scale multi-label classification and question answering in biomedicine. In CLEF (Working Notes)
Pereira MH et al (2015) SAPTE: a multimedia information system to support the discourse analysis and information retrieval of television programs. Multimedia Tools and Applications 74(23):10923–10963
Ritchey KJ (1996) Panoramic image based virtual reality/telepresence audio-visual system and method. Google Patents
Stoilos G, Stamou GB (2014) Hybrid query answering over OWL ontologies. In ECAI
Stoyanchev S, Song YC, Lahti W (2008) Exact phrases in information retrieval for question answering. In Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for Question Answering. Association for Computational Linguistics
Vaughn E (2002) User attitude as a mediator of learning performance improvement in an interactive multimedia environment: an empirical investigation of the degree of interactivity and learning styles.(multimedia). Tech Commun 49(2):258–259
Verbert K et al (2012) Context-aware recommender systems for learning: a survey and future challenges. IEEE Trans Learn Technol 5(4):318–335
Weichselbraun A, Streiff D, Scharl A (2015) Consolidating heterogeneous Enterprise data for named entity linking and web Intelligence. Int J Artif Intell Tools 24(2):1540008
Wen D, Cuzzola J, Brown L (2012) Instructor-aided asynchronous question answering system for online education and distance learning. The International Review of Research in Open and Distributed Learning 13(5):102–125
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This paper was supported by Wonkwang University in 2017.
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Iqbal, M.M., Saleem, Y., Naseer, K. et al. Multimedia based student-teacher smart interaction framework using multi-agents in eLearning. Multimed Tools Appl 77, 5003–5026 (2018). https://doi.org/10.1007/s11042-017-4615-z
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DOI: https://doi.org/10.1007/s11042-017-4615-z