The revolution of Information and Communication Technologies (ICT) has enormously impacted the world. E-learning systems are superseding face-to-face learning. According to the 2019 statistics paper by the Sri Lankan ministry of education, the yearly failure rate of an Ordinary Level Mathematics subject is 33.08% which is higher than other subjects. We aim to introduce appropriate and equitable online learning methods for the 13-16 age group where they can build their self-studying abilities with more accurate methods and good confidence. Many students have poor mathematical skills as they do not have accurate and appropriate instructions for their studies. This system will assist students in developing their mathematical knowledge and skills gradually using video tutorials, examples, and tests. When they have a problem or challenging situation, a virtual assistant can help them to solve their difficulties. The proposed virtual tool will help students reduce the boredom they feel while solving mathematical equations or lessons by distracting them with a mathematically based fun game. Some students may not enjoy studying when teachers or parents sit beside them and focus on them. This tool has the ability to make the students keep focused on the lesson without letting them distract from mathematics by making it fun and simple. Therefore, the proposed system utilizes an attention monitoring system to capture student movements and emotions during the learning process. This solution will be highly customizable since it introduces automatic theory and quiz generation.

Self-learning, Mathematics, Hybrid voice assistant, Play and learn, Emotion capturing, Auto-generated quizzes

[1] Tiwari, Mamta, and S. Dutta. “Sentimental Analysis of Online Study of College and School Going Students.”International Journal of Computer Sciences Engineering. Vol. 9, No. 12, pp. 34-42, 2021.
[2] H. Yang and C. Meinel, "Content-Based Lecture Video Retrieval Using Speech and Video Text Information," IEEE Transactions on Learning Technologies, Vol. 7, No. 2, pp. 142-154, 2014.
[3] Kamal K. Sethi, Praveen Bhanodia, "A Case Study of Online Learning Tools to Mitigate the Impact of Covid-19 Pandemic on Education System", International Journal of Computer Sciences and Engineering, Vol. 8, Issue. 6, pp. 112-115, 2020.
[4] C. Goyal, "Semantic analysis," Analytics Vidhya, India, pp. 9-22, 2021.
[5] K. Radinsky, E. Agichtein, E. Gabrilovich, and S. Markovitch, "A word at a time: computing word relatedness using temporal semantic analysis," in Proceedings of the 20th international conference on World wide web - WWW `11, India, 2011.
[6] M. Z. Mohamed, “Artificial intelligence in mathematics education: A systematic literature review”, International Electronic Journal of Mathematics Education, Vol. 17, Issue. 3, pp. 1-11, 2022.
[7] Kelly, Daniel, “What Do We Know about Khan Academy? A Review of the Literature and Justification for Further Study”, Research Gate, United States, pp. 2-8, 2016.
[8] J. Grossman, Z. Lin, H. Sheng, J. T. Z. Wei, J. J. Williams, S. Goel, “MathBot: Transforming Online Resources for Learning Math into Conversational Interactions”, United States, pp. 1-8, 2019.
[9] A. M. Rahman, A. A. Mamun and A. Islam, “Programming challenges of chatbot: Current and future prospective”, “2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)”, pp. 75-78, 2017.
[10] O. Knill, & J. Carlsson & A. Chi & M. Lezama, “An artificial intelligence experiment in college math education”, Research Gate, United States, pp. 2-9, 2004.
[11] C. A. Corneanu, M. O. Simón, J. F. Cohn and S. E. Guerrero, "Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications," in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 38, No. 8, Spain, pp. 1548-1568, 2016.
[12] P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR, USA, pp. I-I, 2001.
[13] M.Tanaya, A.Majumdar, and Q. M. Jonathan "Face recognition by curvelet based feature extraction", International Conference Image Analysis and Recognition, Germany, pp. 806-817, 2007.
[14] P.Ekman, W.V.Friesen. "Constants across cultures in the face and emotion." Journal of personality and social psychology, No. 2, pp. 1-4, 1971.
[15] M. Sajid, N. I. Ratyal, N. Ali, B. Zafar, S. H. Dar, M. T. Mahmood, Y. B. Joo, "The Impact of Asymmetric Left and Asymmetric Right Face Images on Accurate Age Estimation", Mathematical Problems in Engineering, Vol. 2019, ArticleID 8041413, pp. 10-11, 2019.
[16] Y. M. Cheng and P. F. Chen, “Building an online game-based learning system for elementary school”, International Conference on Intelligent Information Hiding and Multimedia Signal Processing, China, pp. 35-38, 2008.
[17] J. Brandao and V. Carvalho, “‘GAME QUIZ’ - Implementing a serious game platform based in quiz games for the teaching of information and technology,” in 2014 11th International Conference on Remote Engineering and Virtual Instrumentation (R.E.V.), Portugal, pp. 47–50, 2014.
[18] M. F. Ahmad, N. Zakaria, W. A. S. Wan Hassan, S. S. Razali, N. N. Abd Mutalib, and N. Bokhari, “Educational game platform kahoot! In teaching and learning process: A case study of new norms,” in 2021 IEEE 9th Conference on Systems, Process and Control (I.C.S.P.C. 2021), Malaysia, pp. 147-152, 2021.
[19] P. Juric, M. Matetic, and M. Brkic, “Data mining of computer game assisted e/m-learning systems in higher education,” in 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (M.I.P.R.O.), Croatia, pp. 750-755, 2014.