William Tarimo

William Tarimo's research explores how technology and agile methodologies can be used to improve academic outcomes through applications in the learning and teaching processes.

Taking inspiration from his dissertation, Computer-Supported Agile Teaching (CSAT), Tarimo sees the discovery of optimal learning and teaching outcomes as a dynamic and non-static process that has to be discovered through continuous transparency of goals and methods; continuous inspection of the progress and suitability of the methods in achieving the goals; and finally, continuous adaptation of the learning/teaching methods, resources and attitudes. Ultimately, he would like to see teaching and learning to be aware and responsive to the suitability of methods, individual learners’ capabilities, the instructor’s capabilities and the nature of the competencies to be mastered. This agility should be realized from within one to several class meetings and on to the discovery of patterns and best practices over long stretches of the course.

We take advantage of technology in making all these feasible, effective and efficient, and thus part of his research involves the design and development of educational technologies (EdTech), such as Discovery Teaching.

The future of his research will go further into incorporating data analytics, artificial intelligence, customized instruction, intervention and mentoring, and more accurate learner modeling.

Tarimo is also interested in researching robotics design and control, such as autonomous robotics and generation of control instructions (e.g. gaits) through machine learning and computer vision.

Courses that he will be teaching at Connecticut College include Introduction to Computer Science and Problem Solving, Data Structures, Mobile App Development, and Web Technologies & Development.

Recent publications

Dissertation

• “Computer-Supported Agile Teaching (CSAT)”, Doctoral Dissertation, Brandeis University, 08/31/2016

Journal & Conference Publications

• Tarimo, William T., and Timothy J. Hickey. "GroupWork: Learning During Collaborative Assessment Activities." Philadelphia, PA: International Society of the Learning Sciences., 2017.
• Tarimo, William T., and Timothy J. Hickey. "Fully integrating remote students into a traditional classroom using live-streaming and TeachBack." Frontiers in Education Conference (FIE), 2016 IEEE. IEEE, 2016.
• Tarimo, William T., Fatima Abu Deeb, and Timothy J. Hickey. "A Flipped Classroom with and without Computers." International Conference on Computer Supported Education. Springer International Publishing, 2015.
• Tarimo, William T., Fatima Abu Deeb, and Timothy J. Hickey. "Early detection of at-risk students in CS1 using TeachBack/Spinoza." Journal of Computing Sciences in Colleges 31.6 (2016): 105-111.
• William T. Tarimo, Fatima Abu Deeb, and Timothy J. Hickey, “Computers in the CS1 Classroom," Proceedings of the 7th International Conference on Computer Supported Education, 2015, pp. 67–74.
• Tarimo, William T., and Timothy J. Hickey. "Adopting a ‘Flipped’ Interactive Pedagogy using TeachBack: Tutorial Presentation." Journal of Computing Sciences in Colleges 30.6 (2015): 135-137.
• Hickey, Timothy J., and William T. Tarimo. "The Affective Tutor." Journal of Computing Sciences in Colleges 29.6 (2014): 50-56.
• Parker, Gary B., and William T. Tarimo. "Using Cyclic Genetic Algorithms to Learn Gaits for an Actual Quadruped Robot Systems." Man, and Cybernetics (SMC), 2011 IEEE International Conference on. IEEE, 2011.
• Parker, Gary B., William T. Tarimo, and Michael Cantor. "Quadruped Gait Learning Using Cyclic Genetic Algorithms." 2011 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2011.
• Parker, Gary B., and William T. Tarimo. "The Effects of Using a Greedy Factor in Hexapod Gait Learning." 2011 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2011.

Book Chapters

• William T. Tarimo, Fatima Abu Deeb, and Timothy J Hickey, “A 'Flipped Classroom with and without Computers”, International Conference on Computer Supported Education, Springer International Publishing, 2015, pp. 333–347.

Visit the computer science website.

Major or minor in computer science.