Inspiring Students with Inquiry-Guided Learning

Featured Instructors: 

Denise Szecsei, Ph.D., lecturer in math and computer science

Overview:

Improve student motivation and understanding with inquiry-guided learning.

Benefits:

  • Promotes critical thinking, problem-solving, and team-work skills
  • Builds student interest and motivation
  • Improves student understanding

Description:

Denise Szecsei uses interdisciplinary, inquiry-guided learning to promote authentic learning. By allowing her students to identify problems and solutions as part of their efforts to program robots to perform artistically, she encourages higher order thinking skills, such as application, analysis, synthesis, and evaluation.   

 

Inquiry-Guided Learning: Benefits & Examples

The performing robots classes are interdisciplinary, inquiry-guided courses in which students collaborate in groups to program robots to perform original creative content. The classes culminate in live, public performances in which the robots perform choreographed dances, plays, and other original pieces. The class is part of a larger intellectual conversation about interdisciplinarity and more specifically the relationship between the arts and STEM (Science, Technology, Engineering, Math) fields, with some scholars advocating an integration of the arts through a new acronym, STEAM. Professor Szecsei taught the original performing robots classes primarily to juniors and seniors, but she has also taught it as a First Year Seminar.

In 2013 George de la Peña (Dance) and Alberto Segre (Computer Science) won an Innovations in Teaching With Technology Award (ITTA) grant from The University of Iowa Academic Technologies Advisory Council that helped to fund the purchase of robots for the course. Professor Szecsei (Computer Science and Mathematics) collaborated with various other faculty members in the development and facilitation of the course. Dance instructor Charlotte Adams helped students to contemplate how robots that are incapable of exhibiting facial expressions could use posture and body movement to show emotion. Theatre professor Bryon Winn explained important aspects of monologue delivery and the process of trying out for a theatrical production. Other colleagues from Computer Sciences, Theatre, and Dance attended performances to provide constructive feedback about the pieces the students create. 

The class benefits students in a number of ways:

  • Computer science students got practical experience translating their disciplinary knowledge for non-experts, a skill that is crucial in fields that work with clients. For example, the computer science students figured out that choreography which required repetitive movements lasting an unspecified amount of time could be accomplished through a “for-loop,” and they worked with dance students to create that programming.   
  • Performing arts students gained perspective on their fields. The robots lack facial expression, so students created other ways of performing emotion. Applying algorithmic thinking to deconstructing a dance move in order to program a robot to do it, gave dance students a better understanding of movement.
  • Collaborative work allows students to learn from their peers. Often fellow novices are better able to explain common misconceptions or other disciplinary bottlenecks than are experts in a field. 
  • Professor Szecsei has found that the class helps students to understand that artistic creativity and problem-solving skills are closely linked, and that connection promotes confidence in students from supposedly widely divergent fields. 

Inquiry-Guided Learning: Best Practices

Students are most comfortable in group-work assignments that are structured to require contributions from all students.  This prevents dysfunctional situations in which some students “slack” or others dominate the group. Professor Szecsei’s students needed to work collaboratively to hold the robots into position, analyze the components of speech and movement, and offer ideas about both artistic expression and computer programming.

Professor Szecsei operated as a “guide on the side” rather than a “sage on the stage”:  When the students wanted the robots to be able to respond to each other, Professor Szecsei directed students to resources about routers, Raspberry Pis, and Python chat scripts.  Both the students and Professor Szecsei enjoyed this process more than if she had simply delivered a lecture on networking.   

Professor Szecsei’s students often record the robots performing so the class can assess how the programming might be improved.  Providing opportunities to reflect on learning, whether through writing or through group analysis of a video can help ensure that all students are making important intellectual connections.    

Professor Szecsei recommends designing a system for documenting which students collaborated on which part, and she also implemented peer-assessment in which students gave feedback on how their peers were contributing to the projects.  Practitioners find that student buy-in is improved when students understand how they will be graded.  Practitioners recommend discussing the grading system with students, especially in team-based learning.  Furthermore, this rubric from the UI Center for Teaching offers some ideas for grading problem-based learning assignments.

Inquiry-Guided Learning: Bibliography & Related Content

Bibliography

Lee, V. S. (2012) “What Is Inquiry-Guided Learning?” Inquiry Guided Learning: New Directions for Teaching and Learning, no. 129.  San Francisco, CA: Jossey-Bass.

Michaelsen, L. K., Knight, A. B. & Fink, L. D., eds. (2002) Team-Based Learning: A Transformative Use of Small Groups in College Teaching. Westport, CT: Praeger.

Szecsei, D. (2015) Robot Theater. Retrieved from https://robottheater.wordpress.com/

Team-Based Learning Collaborative. (2016) TBLC. Retrieved from http://www.teambasedlearning.org

The University of Iowa Computer Science Program. (2016) UI CS Performing Robots. The University of Iowa. Retrieved from https://www.cs.uiowa.edu/resources/ui-cs-performing-robots

​The University of Iowa ITS. (2016) Innovations in Teaching with Technology Awards. The University of Iowa. Retrieved from http://its.uiowa.edu/itta

​Related Content

The Performing robots courses use five NAO robots, which are programmed in Choregraphe, a programming software accessible to beginners as well as experienced coders.   

Learning Style Preferences -- Explore best practices for helping students to identify what they need to know and then applying it. 

Designing and Facilitating Group Work -- Explore the pedagogical benefits of collaborative learning and get advice on setting up groups, designing effective assignments, grading, promoting student buy-in for group work, and more. 

Motivating Student Learning -- Help students tap their intrinsic desire to learn.

Resources 
LINK
Obermann Center for Advanced Studies
​The University of Iowa Obermann Center for Advanced Studies encourages innovation, cross-disciplinary and collaborative scholarship and teaching, and engagement with local and global communities.