inventado

Paul Salvador Inventado

Post-doctoral researcher, School of Design, Carnegie Mellon University
5000 Forbes Avenue, Pittsburgh, PA 15213
pinventado@cmu.edu
+1 412-268-2825

Profiles: Google Scholar, LinkedIn

 

I am a post-doctoral researcher in the School of Design at Carnegie Mellon University. Currently, I am working on an NSF-funded project with my supervisor Peter Scupelli in collaboration with Ryan Baker at University of Pennsylvania, and Neil Heffernan III at Worcester Polytechnic Institute. The goal of the project is to make math tutors more engaging and effective through Design patterns uncovered from the results of educational data mining techniques.  

I was a recipient of the Monbukagakusho (Japanese government) scholarship and received my PhD degree from Osaka University under the supervision of Prof. Masayuki Numao. My dissertation focused on helping students manage their learning behavior through a self-regulation support tool.  

I was an Assistant Professor under the Software Technology Department at De La Salle University, Philippines from 2005-2014. I was a founding member of the Center for Empathic Human-Computer Interaction, and am still actively collaborating with the team.

I am also the webmaster of the International Educational Data Mining Society’s website.

Please find my full CV here.  

Educational Background

Non-degree. Carnegie Mellon University, USA
courses taken: E-Learning Design Principles and Methods, Applied Machine Learning		  2016
Ph.D. Information Science and Technology, Osaka University, Japan  2014
 M.S. Computer Science, De La Salle University, Philippines  2007
B.S. Computer Science, De La Salle University, Philippines  2005


Publications

Journals

  1. Inventado, P.S. and Scupelli, P. (2015). Towards an open, collaborative repository for online learning system design patterns, eLearning Papers 42(1): 14-27.
  2. Inventado, P. S., Legaspi, R., Moriyama, K., Fukui, K. I., and Numao, M. (2014). Sidekick: A Tool for Helping Students Manage Behavior in Self-initiated Learning Scenarios. International Journal of Distance Education Technologies (IJDET), 12(4), 32-54.
  3. Cabredo, R., Legaspi, R. S., Inventado, P. S., and Numao, M. (2013). Discovering Emotion-Inducing Music Features Using EEG Signals. Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII), 17(3), 362-370.
  4. Inventado, P. S., Legaspi, R., Suarez, M., and Numao, M. (2011). Predicting student emotions resulting from appraisal of ITS feedback. Research and Practice in Technology Enhanced Learning, 6(2):107-133.

 

Book chapters

  1. Baker, R.S. and Inventado, P.S. (2016). Educational data mining and learning analytics: Potentials and possibilities for online distance education. In G. Veletsianos (Ed.), Emergence and Innovation in Digital Learning: Foundations and Applications (pp. 83-98). Edmonton: Athabasca University Press.
  2. Baker, R. S., Inventado, P.S. (2014). Educational data mining and learning analytics, In Lárusson, J. A. and White, B., editors, Learning Analytics: From Research to Practice, Computer-Supported Collaborative Learning Series.

 

Conference Papers

  1. Inventado, P.S. and Scupelli, P. (2016). Patterns for learning-support design in math online learning systems. In Proceedings of the 23rd Conference on Pattern Languages of Programs (PLoP 2016). ACM.
  2. Inventado, P.S. and Scupelli, P. (2016). Design patterns for helping students to learn to represent math problems in online learning systems. In Proceedings of the 21st European Conference on Pattern Languages of Programs (EuroPLoP 2016). ACM.
  3. Inventado, P.S. and Scupelli, P. (2016). Design patterns for math problems and learning support in online learning systems. In Proceedings of the 21st European Conference on Pattern Languages of Programs (VikingPLoP 2016). ACM.
  4. Slater, S., Ocumpaugh, J., Baker, R., Scupelli, P., Inventado, P.S., Heffernan, N. (2016) Semantic Features of Math Problems: Relationships to Student Learning and Engagement. In Proceedings of the 9th International Conference on Educational Data Mining (pp. 223-230).
  5. Inventado, P.S. and Scupelli, P. (2015). Data-driven design pattern production: A case study on the assistments online learning system. In Proceedings of the 20th European Conference on Pattern Languages of Programs (EuroPLoP 2015). ACM.
  6. Inventado, P.S. and Scupelli, P. (2015). A Data-driven methodology for producing online learning system design patterns. In Proceedings of the 22nd Conference on Pattern Languages of Programs (PLoP 2015). ACM.
  7. Inventado, P. S., Legaspi, R., Cabredo, R., and Numao, M. (2013). Sidekick retrospect: A self-regulation tool for unsupervised learning environments. In Theory and Practice of Computation (Volume 7 of Proceedings of Information and Communications Technology) (pp. 195-205). Springer Japan.
  8. Inventado, P.S., Legaspi, R., Moriyama, K., Fukui, K., and Numao, M. (2013). Modeling affect in self-directed learning scenarios. In Proceedings of 4th Int’l Workshop on Empathic Computing.
  9. Inventado, P.S., Legaspi, R., Moriyama, K., Fukui, K., Numao, M. (2013). Building policies for supportive feedback in self-directed learning scenarios. In Proceedings of Workshop on Computation: Theory and Practice (pp. 144-155). World Scientific.
  10. Inventado, P.S., Legaspi, R., Moriyama, K., Fukui, K., Numao, M. (2013). An architecture for identifying and using effective learning behavior to help students manage learning. In AIED Workshop Proceedings: Formative Feedback in Interactive Learning Environments.
  11. Vachiratamporn, V., Inventado, P.S., Legaspi, R., Moriyama, K., & Numao, M. (2013). An analysis of affective state transitions in survival horror game with the aid of player self-reports and physiological signals. In Proceedings of The 27th Annual Conference of the Japanese Society for Artificial Intelligence.
  12. Cabredo, R., Legaspi, R. S., Inventado, P. S., and Numao, M. (2012). An Emotion Model for Music Using Brain Waves. In 13th International Society for Music Information Retrieval Conference (ISMIR) (pp. 265-270).
  13. Inventado, P. S., Legaspi, R., Cabredo, R., and Numao, M. (2012). Modeling affect and intentions in unsupervised learning environments. In Proceedings of the 3rd Int’l Workshop on Empathic Computing.
  14. Inventado, P. S., Legaspi, R., Cabredo, R., and Numao, M. (2012). Student learning behavior in an unsupervised learning environment. In Proceedings of the 20th International Conference on Computers in Education (pp. 730-737). (Best Technical Design Paper Award)
  15. Inventado, P. S., Legaspi, R., Suarez, M., and Numao, M. (2012). Categorizing and comparing behaviors of students engaged in self-initiated learning online. In Theory and practice of computation (Volume 5 of Proceedings in Information and Communications Technology) (pp. 133-144). Springer, Japan.
  16. Mai, A., Legaspi, R., Inventado, P.S., Cabredo, R., Kurihara, S., & Numao, M. (2012). A Model for Sitting Postures in Relation to Learning and Non-learning Behaviors. In Proceedings of The 26th Annual Conference of the Japanese Society for Artificial Intelligence.
  17. Inventado, P.S., Legaspi, R., Suarez, M., and Numao, M. (2011). Investigating transitions in affect and activities for online learning interventions. In Proceedings of the 19th Conference on Computers in Education (pp. 571-578). (Nominated for Best Student Paper Award)
  18. Inventado, P. S., Legaspi, R., Suarez, M., and Numao, M. (2011). Observatory: A tool for recording, annotating and reviewing emotion-related data. In Third International Conference on Knowledge and Systems Engineering (pp. 261-265). IEEE.
  19. Azcarraga, J., Suarez, M.T., and Inventado, P.S. (2010). Predicting the Difficulty Level Faced by Academic Achievers based on Brainwave Analysis. In Proceedings of the 18th International Conference on Computers in Education (pp. 107-109).
  20. Cu, J., Cabredo, R., Cu, G., Legaspi, R., Inventado, P.S., Trogo, R., and Suarez, M. T. (2010). The TALA empathic space: integrating affect and activity recognition into a smart space. In 3rd International Conference on Human-Centric Computing (HumanCom) (pp. 1-6). IEEE.
  21. Inventado, P. S., Legaspi, R., Bui, T. D., and Suarez, M. (2010). Predicting student’s appraisal of feedback in an ITS using previous affective states and continuous affect labels from EEG data. In Proceedings of the 18th International Conference on Computers in Education (pp. 71-75).
  22. Inventado, P.S., Suarez, M.T. and Legaspi, R. (2010). Tracking and modelling the behavior of students in learning online. In Proceedings of the 10th Philippine Computing Science Congress.
  23. Inventado, P.S., Suarez, M., and Legaspi, R. (2010). Identifying student appraisal of feedback provided by an ITS using system logs and brainwave data. In Proceedings of the 15th Joint Academic Research Symposium of De La Salle and Osaka University.
  24. Inventado, P.S. (2009). Tracking digital natives’ online learning behavior. In Proceedings of the Osaka University – De La Salle University Academic Research Workshops.
  25. Inventado, P.S. and See, S. (2009). Ai Cap’n: A game platform for learning artificial intelligence. In Proceedings of 2009 9th Philippine Computing Science Congress.
  26. Roxas, R., Inventado, P.S., Asenjo, G., Corpus, M., Dita, S., Sison-Buban, R. and Taylan, D. (2009). Online corpora of Philippine languages. In Proceedings of the 2009 DLSU Art Congress.

 

Poster Presentations

  1. Inventado, P.S., Scupelli, P., Van Inwegen, E., Ostrow, K., Heffernan, N., Baker, R.S., Slater, S., Almeda, M.V., Ocumpaugh, J. (2016). Hint Availability slows completion times in summer work. In Proceedings of the 9th International Conference on Educational Data Mining (pp. 388-393).
  2. Inventado, P.S. and Scupelli, P. (2016). A data-driven design pattern methodology to facilitate effective pedagogical practice in online learning systems. Poster session presented at: CMU Teaching and Learning Summit, Pittsburgh, PA, USA.
  3. Inventado, P.S. and Scupelli, P. (2015). Addressing MOOCs’ sustainability issues using data-driven design pattern production. Poster session presented at: Learning with MOOCs II, New York, NY, USA.
  4. Inventado, P.S., Legaspi, R., Moriyama, K., Fukui, K., Numao, M. (2013). Identification of effective learning behaviors. In Artificial Intelligence in Education (Volume 7926 of Lecture Notes in Computer Science) (pp. 670-673). Springer Berlin Heidelberg.
  5. Inventado, P.S., Legaspi, R., Moriyama, K., Fukui, K., Numao, M. (2013). Building Incremental Affect Models to Help Students Annotate and Analyze their their Behavior in Self -Directed Learning Scenarios. In Proceedings 20th Conference on Computers in Education, pp. 170-172, Bali, Indonesia.
  6. Inventado, P.S., Legaspi, R. S., Suarez, M., and Numao, M. (2011). Investigating the transitions between learning and non-learning activities as students learn online. In Pechenizkiy, M., Calders, T., Conati, C., Ventura, S., Romero, C., and Stamper, J. C., editors, 4th International Conference on Educational Data Mining, pp. 367-368, Eindhoven, The Netherlands.
  7. Inventado, P.S., Suarez, M.T. & Legaspi, R. (2009). Modelling Digital Natives in Social Learning Environments. In Proceedings of the 17th International Conference on Computers in Education 2009, HKSAR, Hong Kong.
  8. Legaspi, R., Inventado, P.S., Cabredo, R., & Numao, M. (2012). Aiding digital natives learn positive learning behaviors through reflection. In Proceedings of the 20th International Conference on Computers in Education (ICCE 2012) (pp. 806-810).

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