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Dr. Shashi Kant Shankar

Assistant Professor, Department of Cognitive Sciences and Psychology, Amritapuri

Qualification: Ph.D

Bio

Dr. 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 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.

Publications

Journal Article

Year : 2024

How to Build More Generalizable Models for Collaboration Quality? Lessons Learned from Exploring Multi-Context Audio-Log Datasets using Multimodal Learning Analytics.

Cite this Research Publication : 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

Year : 2023

Multimodal Learning Analytics research in the wild: challenges and their potential solutions

Cite this Research Publication : 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.

Year : 2023

CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions

Cite this Research Publication : Shankar, S.K., Ruiz-Calleja, A., Prieto, L.P., Rodríguez-Triana, M.J., Chejara, P., & Tripathi, S. (2023), 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

Year : 2022

Exploring the triangulation of dimensionality reduction when interpreting multimodal learning data from authentic settings

Cite this Research Publication : 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

Year : 2022

CDM4MMLA: Contextualized Data Model for MultiModal Learning Analytics. In the Multimodal Learning Analytics Handbook

Cite this Research Publication : 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

Year : 2022

A Set of Evidence-based Guidelines for Planning Authentic Multimodal Learning Analytics Situations by Involving Cross-Disciplinary Stakeholders

Cite this Research Publication : 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, [2022]

Year : 2021

CoTrack2: A tool to track collaboration across physical and digital spaces with real time activity visualization

Cite this Research Publication : 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/
[2020]

Year : 2021

EFAR-MMLA: An evaluation framework to assess and report generalizability of machine learning models in MMLA

Cite this Research Publication : 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

Year : 2021

Teachers’ reflections on students’ learning approaches who resumed physical classrooms after almost two years due to COVID-19 pandemic-induced disruptions

Cite this Research Publication : 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
[2021]

Year : 2020

Quantifying collaboration quality in face-to-face classroom settings using MMLA

Cite this Research Publication : 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
[2019]

Year : 2020

A Multimodal Learning Analytics approach to support evidence-based teaching and learning Practices

Cite this Research Publication : 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

Year : 2020

Challenges in multichannel data discovery and integration for monitoring performance in self-regulated learning

Cite this Research Publication : 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/

Year : 2020

Cotrack: A tool for tracking collaboration across physical and digital spaces in collocated blended settings

Cite this Research Publication : 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/

Year : 2020

MMLA approach to track collaborative behavior in face-to-Face blended settings

Cite this Research Publication : 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/

Year : 2020

Curriculum analytics as a communication mediator among stakeholders to enable the discussion and inform decision-making

Cite this Research Publication : 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/

Year : 2020

A scalable architecture for the dynamic deployment of Multimodal Learning Analytics applications in smart classrooms

Cite this Research Publication : 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

Year : 2020

Multimodal Data Value Chain (M-DVC): A conceptual tool to support the development of Multimodal Learning Analytics solutions

Cite this Research Publication : 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). https://doi.org/10.1109/RITA.2020.2987887

Year : 2019

An architecture and data model to process multimodal evidence of learning

Cite this Research Publication : 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
[2018]

Year : 2019

A data value chain to model the processing of multimodal evidence in authentic learning scenarios

Cite this Research Publication : 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).

Year : 2018

A review of multimodal learning analytics architectures

Cite this Research Publication : 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
[2017]

Publisher : IEEE

Year : 2016

Optimization of energy dissipation in direct-diffusion two-level low energy adaptive clustering hierarchy routing protocol

Cite this Research Publication : 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).
[2015]

Year : 2016

To detect and isolate zombie attack in cloud computing

Cite this Research Publication : 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).

Year : 2016

Enhanced image based authentication with secure key exchange mechanism using ECC in cloud

Cite this Research Publication : 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

Year : 2016

An efficient algorithm for generating association rules by using constrained itemsets mining

Cite this Research Publication : 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

Publisher : IEEE

Year : 2016

Constraint data mining using apriori algorithm with AND operation

Cite this Research Publication : 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

Publisher : IEEE

Year : 2016

A survey on wireless body area network and electronic-healthcare

Cite this Research Publication : 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

Year : 2016

Typical and atypical hierarchical routing protocols for WSNs: A review

Cite this Research Publication : 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

Year : 2016

Secure medical data transmission in Wireless Body Area Network

Cite this Research Publication : Shankar, S. K., & Tomar, A. S. (2017). Secure medical data transmission in Wireless Body Area Network. In LAMBERT proceedings (Master's thesis). LAMBERT.
[2016]

Year : 2015

Secure medical data transmission by using ECC with mutual authentication in WSNs

Cite this Research Publication : 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

Projects Involved

“1. Developing a Teacher Professional Development program to train university teachers for adopting Educational Technology in their daily teaching practice to support active learning in classrooms
2. Creation of Simulated Skill Training Packages (Skill E-Labs) for Vocational Education and Training (VET)”

Conference Attended

ICALT, ICWL, EC-TEL, LAK, JTELSS

Academic Activities
  • “Professional membership – IEEE, SoLAR, EATEL
  • Reviewer – Frontiers of Education, EC-TEL, LAK, AIED”
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