Our Response to COVID-19

Dr.Shashi Kant Shankar

Biography


Before joining Amrita, Shashi Kant Shankar earned his Ph.D. from the School of Digital Technologies at Tallinn University in Estonia, European Union. He was also working as a researcher in the Centre for Educational Technology at Tallinn University. Shankar's research aimed to support the development of context-aware and reusable Multimodal Learning Analytics solutions in authentic scenarios involving multiple cross-disciplinary stakeholders. His dissertation was linked to Tallinn University's goal of promoting lifelong learning. Shanker used design-based research methodology in his Ph.D. dissertation and scoped it under the pragmatic constructivism paradigm. Shashi Kant Shankar was born and raised in Bihar, India. He received his bachelor's degree in Information Technologies from Kuvempu University in 2011, and went on to earn a master's degree in Computer Applications from Sikkim Manipal University in 2014 and a second master's degree in Computer Science and Engineering (please access thesis here) from Lovely Professional University in 2016. In addition to his academic credentials, Shankar has completed a professional diploma in software engineering from NIIT. He has software development experience using the .NET framework with C# and SQL Server. He has also been a professional IT trainer at NIIT for two and a half years. Shashi Kant Shankar believes that education is an inoculation against disruption. He also believes that healthy discussion and teamwork are essential for reaching milestones in the endless journey of life and positively contributing to the global society. He values equity and encourages independent thinking within the framework of democracy. Shashi Kant Shankar enjoys a variety of activities - reading books, spending time in nature, discussing research with colleagues, socializing with friends, cooking for family and friends, playing sports, watching movies and television shows, staying informed about current events, and many more.

ASSISTANT PROFESSOR

Publications

1. Shankar, S.K., Ruiz-Calleja, A., Prieto, L.P., Rodríguez-Triana, M.J., Chejara, P., & Tripathi, S. (2023), href="#">CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions. JUCS - Journal of Universal Computer Science 29(3): 265-297.
https://doi.org/10.3897/jucs.84558
2. Chejara, P., Prieto, L. P., Ruiz-Calleja, A., Rodríguez-Triana, M. J., Shankar, S. K., & Kasepalu, R. (2021). EFAR-MMLA: An evaluation framework to assess and report generalizability of machine learning models in MMLA. Sensors, MDPI 21(8), 2863. https://doi.org/10.3390/s21082863
3. Shankar, S. K., Rodríguez-Triana, M. J., Ruiz-Calleja, A., Prieto, L. P., Chejara, P., & Martínez-Monés, A. (2020). Multimodal Data Value Chain (M-DVC): A conceptual tool to support the development of Multimodal Learning Analytics solutions. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 15(2), (pp. 113-122).
4. Huertas Celdrán, A., Ruipérez-Valiente, J. A., Garcia Clemente, F. J., Rodríguez-Triana, M. J., Shankar, S. K., & Martinez Perez, G. (2020). A scalable architecture for the dynamic deployment of Multimodal Learning Analytics applications in smart classrooms. Sensors, MDPI, 20 (10), 2923. https://doi.org/10.3390/s20102923

1. Chejara, P., Prieto, L. P., Rodríguez-Triana, M. J., Ruiz-Calleja, A., Kasepalu, R., & Shankar, S.K. (2023, March). How to Build More Generalizable Models for Collaboration Quality? Lessons Learned from Exploring Multi-Context Audio-Log Datasets using Multimodal Learning Analytics. In LAK23: 13th International Learning Analytics and Knowledge Conference (LAK2023). ACM, USA, 111–121.
https://doi.org/10.1145/3576050.3576144

2. Chejara, P., Kasepalu, R., Prieto, L. P., Rodríguez-Triana, M. J., Ruiz-Calleja, A., & Shankar, S.K. (2023, March), Shankar, S.K.,.. Multimodal Learning Analytics research in the wild: challenges and their potential solutions. In CEUR Workshop proceeding of CrossMMLA'23.

3. Shankar, S.K., & Sasi, D. (2023), A Set of Evidence-based Guidelines for Planning Authentic Multimodal Learning Analytics Situations by Involving Cross-Disciplinary Stakeholders. Dykinson, ISBN 978-84-1170-558-5.

4. Shankar, S. K., Tripathi, S., Nupur, N., & Chejara, P. (2022, July). Teachers' reflections on students’ learning approaches who resumed physical classrooms after almost two years due to COVID-19 pandemic-induced disruptions. In the 14th International Conference on Education and New Learning Technologies (EDULEARN 2022). IATED (pp. 1656-1664). https://doi.org/10.21125/edulearn.2022.0437

5. Chejara, P., Prieto, L. P., Ruiz-Calleja, A., Rodríguez-Triana, M. J., Shankar, S. K., & Kasepalu, R. (2021). CoTrack2: A tool to track collaboration across physical and digital spaces with real time activity visualization. In Companion Proceedings of the 11th International Conference on Learning Analytics & Knowledge (LAK 2021). SoLAR (pp. 406-406). https://www.solaresearch.org/core/lak21-companion-proceedings/

6. De Silva, L. M. H., Rodríguez-Triana, M. J., Chounta, I., Tammets, K., Shankar, S. K. (2020, March). Curriculum analytics as a communication mediator among stakeholders to enable the discussion and inform decision-making. In Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK 2020). SoLAR (pp. 762-764). https://www.solaresearch.org/core/lak20-companion-proceedings/

7. Chejara, P., Kasepalu, R., Shankar, S. K., Prieto, L. P., Rodríguez-Triana, M. J., & Ruiz-Calleja, A. (2020, March). MMLA approach to track collaborative behavior in face-to-Face blended settings. In Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK 2020). SoLAR, (pp. 543-548). https://www.solaresearch.org/core/lak20-companion-proceedings/

8. Chejara, P., Prieto, L. P., Rodríguez-Triana, M., Ruiz-Calleja, A., & Shankar, S. K. (2020, March). Cotrack: A tool for tracking collaboration across physical and digital spaces in collocated blended settings. In Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK 2020). SoLAR, (pp. 186-186). https://www.solaresearch.org/core/lak20-companion-proceedings/

9. Shankar, S. K. (2020, March). Challenges in multichannel data discovery and integration for monitoring performance in self-regulated learning. In Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK 2020). SoLAR, (pp. 455- 458). https://www.solaresearch.org/core/lak20-companion-proceedings/

10. Shankar, S. K., Ruiz-Calleja, A., Prieto, L. P., & Rodríguez-Triana, M. J. (2020, July). A Multimodal Learning Analytics approach to support evidence-based teaching and learning Practices. In IEEE 20th International Conference on Advanced Learning Technologies (ICALT 2020). IEEE, (pp. 381-383). https://doi.org/10.1109/ICALT49669.2020.00120

11. Chejara, P., Prieto, L. P., Ruiz-Calleja, A., Rodríguez-Triana, M. J., Shankar, S. K., & Kasepalu, R. (2020, September). Quantifying collaboration quality in face-to-face classroom settings using MMLA. In International Conference on Collaboration Technologies and Social Computing (CollabTech 2020). Lecture Notes in Computer Science, Springer, Cham, 12324 (pp. 159-166). https://doi.org/10.1007/978-3-030-58157-2_11

12. Shankar, S. K., Calleja, A. R., Iglesias, S. S., Arranz, A. O., Topali, P., & Monés, A. M. (2019, June). A data value chain to model the processing of multimodal evidence in authentic learning scenarios. In CEUR Workshop proceeding of Learning Analytics Summer Institute Spain (LASI 2019). CEUR Proc., 2415 (pp. 71-83).

13. Chejara, P., Prieto, L. P., Ruiz-Calleja, A., Rodríguez-Triana, M. J., & Shankar, S. K. (2019, September). Exploring the triangulation of dimensionality reduction when interpreting multimodal learning data from authentic settings. In European Conference on Technology Enhanced Learning (EC-TEL 2019). Lecture Notes in Computer Science, Springer, Cham, 11722 (pp. 664-667). https://doi.org/10.1007/978-3-030-29736-7_62

14. Shankar, S. K., Ruiz-Calleja, A., Prieto, L. P., Rodríguez-Triana, M. J., & Chejara, P. (2019, September). An architecture and data model to process multimodal evidence of learning. In International Conference on Web-Based Learning (ICWL 2019). Lecture Notes in Computer Science, Springer, Cham, 11841 (pp. 72-83). https://doi.org/10.1007/978-3-030-35758-0_7

15. Shankar, S. K., Prieto, L. P., Rodríguez-Triana, M. J., & Ruiz-Calleja, A. (2018, July). A review of multimodal learning analytics architectures. In IEEE 18th International Conference on Advanced Learning Technologies (ICALT 2018). IEEE, (pp. 212-214). https://doi.org/10.1109/ICALT.2018.00057

16. Shankar, S. K., & Tomar, A. S. (2017). Secure medical data transmission in Wireless Body Area Network. In LAMBERT proceedings. LAMBERT.

17. Kaur, N., Grewal, D. K., & Shankar, S. K. (2016, April). Typical and atypical hierarchical routing protocols for WSNs: A review. In IEEE International Conference on Computing, Communication and Automation (ICCCA 2016). IEEE, (pp. 465-470). https://doi.org/10.1109/CCAA.2016.7813764

18. Shankar, S. K., & Tomar, A. S. (2016, May). A survey on wireless body area network and electronic-healthcare. In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT 2016). IEEE, (pp. 598-603). https://doi.org/10.1109/RTEICT.2016.7807892

19. Shankar, S. K., & Kaur, A. (2016, May). Constraint data mining using apriori algorithm with AND operation. In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT 2016). IEEE, (pp. 1025-1029). https://doi.org/10.1109/RTEICT.2016.7807985

20. Kaur, A., Aggarwal, V., & Shankar, S. K. (2016, May). An efficient algorithm for generating association rules by using constrained itemsets mining. In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT 2016). IEEE, (pp. 99-102). https://doi.org/10.1109/RTEICT.2016.7807791

21. Kaur, S., Tomar, A. S., Shankar, S. K., Sharma, M. (2016). To detect and isolate zombie attack in cloud computing. In International Journal of Control Theory and Applications (pp. 227-238).

22. Grewal, N. K., Grewal, D. K., & Shankar, S. K. (2016). Optimization of energy dissipation in direct-diffusion two-level low energy adaptive clustering hierarchy routing protocol. In International Journal of Control Theory and Applications (pp. 307-315).

23. Shankar, S. K., Tomar, A. S., & Tak, G. K. (2015, December). Secure medical data transmission by using ECC with mutual authentication in WSNs. In Fourth International Conference on Eco-friendly Computing and Communication Systems (ICECCS 2015). Procedia Computer Science, Elsevier, 70, (pp. 455-461). https://doi.org/10.1016/j.procs.2015.10.078

1. Shankar, S. K., Rodríguez-Triana, M. J., Prieto, L. P., Ruiz-Calleja, A., & Chejara, P. (2022). CDM4MMLA: Contextualized Data Model for MultiModal Learning Analytics. In the Multimodal Learning Analytics Handbook. Springer, Cham. https://doi.org/10.1007/978-3-031-08076-0_9

2. Tomar, A. S., Shankar, S. K., Sharma, M., & Bakshi, A. (2016, September). Enhanced image based authentication with secure key exchange mechanism using ECC in cloud. In Security in Computing and Communications (SSCC 2016). Communications in Computer and Information Science, 625 (pp. 63-73). Springer, Singapore. https://doi.org/10.1007/978-981-10-2738-3_6

1. Worked as Junior Researcher at the Center for Educational Technology and Lecturer at the School of Digital Technologies, Tallinn University, Estonia during 2018-21.

2. Worked as a Professional IT Trainer at NIIT Limited during 2012-14 3. Worked as a Software Developer at Savior (Explore Technology) for a year in 2011

 

1. Won Students Innovation Challenge award at the World Haptic Conference 2023, Delft, The Netherlands.
2. PhD thesis was awarded for the Smart Specilization scholarship by Archemedes Foundation to supporting Lifelong Learning of Estonian Society in 2017 for four years.
3. Won the best faculty award in NIIT Kolkata region in 2023-14

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