Exploring Teachers Instructional Choices for Promoting Productive Struggle

• In Event: 35.028 - Failure in the Learning Process: How Learners Experience and Overcome Obstacles Through Resources and Supports

Abstract

Deep learning is often attributed to struggling through an ambiguous or muddy problem (Dewey, 1933; Brownwell and Sims, 1946; Hiebert & Wearne, 2003; Piaget, 1960). It is through persisting that students learn despite experiencing struggle. Kapur (2008, 2016) has called these perplexing moments - “productive failure,” a type of struggle that teachers can use as opportunities to deepen learning when learners work through ill-defined problems. Scholars noted that educators could help students frame struggles in a positive light by encouraging a growth mindset (Yeager & Dweck, 2012) that fosters student persistence or ‘grit’ (Duckworth, 2007). Other scholars such as Rose (2015) point out that solely focusing on character traits (i.e. growth mindset or grit) particularly for marginalized or low-income youth can be detrimental because it shifts the focus away from the structural inequalities that these youth face in their day to day lives. It is important to highlight how instruction can help students take advantage of these deep learning moments. For example, in computer modeling for science education, teachers promote moments of productive struggle through instruction that supports tinkering (Petrich, Wilkinson, & Bevan, 2013) and activities that explore the iterative design process through multiple failed drafts (Ryoo, et. al., 2015; Turkle & Papert, 1990). Learning the ways educators structure such instruction and frame student experiences of failure can broaden our understanding of how productive struggle advances student learning in the classroom (Smith, 2015; Loibl & Rummel, 2014).

In this study, we examine three case studies of teachers implementing a science curriculum designed to teach science inquiry and computational thinking skills in two Southwestern middle schools and one high school. We explore the different instructional strategies taken by these teachers in their attempts to help their students learn to code. We investigate how the teachers’ instructional techniques hinder, develop and frame student experience of learning from failure through productive struggle. Through case study comparisons (Yin, 2017), we illuminate how one teacher not only encouraged tinkering, she shaped coding instruction to advance understanding of scientific concepts.

This study analyzes classroom observation data collected over multiple days of implementation and transcripts/field notes of teacher reflections about their instructional intents. We code teacher’s questioning strategies that shaped student explorations of muddy problems and pushed conceptual learning. Aligning questioning techniques to instructional intent, we highlight the different pedagogical strategies.

In order for deep learning to take place within a classroom, it is more than just providing a safe space to work through ambiguous and perplexing learning experiences. How teachers frame these moments in the instruction can help students learn deeply (Smith, 2015; Loibl & Rummel, 2014). While Kapur (2008) pointed to the importance for students to answer ill-defined problems on their own, here in this poster, we point to the importance of teacher questions and responses that scaffold student struggles productively.

Authors

• Emma Anderson, Massachusetts Institute of Technology

• Ling Hsiao, Massachusetts Institute of Technology

• Irene Lee, Santa Fe Institute