Philip Picton

About

Philip Picton is an engineering educator and researcher whose work spans two interconnected domains: creative problem-solving pedagogy in engineering education and early neural network applications in robotics. His most influential contributions emerged from a sustained investigation into how undergraduate engineers develop and demonstrate creative thinking skills, culminating in a landmark three-year action research project that utilized reusable learning objects and robots as pedagogical tools. This work, which has garnered 44 citations, addressed a critical gap identified in benchmark and policy statements — namely, that while creative problem-solving is widely acknowledged as essential for engineering graduates, institutions offered little practical guidance on fostering or assessing these capabilities. Picton's findings provided concrete, evidence-based strategies for engineering educators grappling with this challenge. His earlier related study further reinforced the persistent deficiencies in how process skills are developed within engineering curricula. Beyond education research, Picton demonstrated breadth through his contributions to neural network applications, exploring Elman recurrent networks for real-time motion prediction in robot navigation systems. Together, these works position Picton as a thoughtful advocate for richer, skills-focused engineering education backed by practical experimentation.

Research Focus

Key Achievements

Top Papers

1. 1
   Problem solving and creativity in engineering: conclusions of a three year project involving reusable learning objects and robots

   44 citations · 2010
2. 2
   Problem solving and creativity for undergraduate engineers: findings of an action research project involving robots

   11 citations · 2008
3. 3
   A neural network motion predictor

   2 citations · 1993

Key Collaborators

Contact & Links