Novice to Postgraduate Researcher Perceptions of Threshold Concepts and Capabilities in Signal Processing: Understanding Students' and Researchers' Perspectives

You are here

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

Novice to Postgraduate Researcher Perceptions of Threshold Concepts and Capabilities in Signal Processing: Understanding Students' and Researchers' Perspectives

By: 
Sally A. Male; Roberto B. Togneri; Lu C. Jin

Signal processing is an engineering discipline known to involve abstract and complex concepts. Curriculum development should be informed by an understanding of the most critical and challenging learning in the field. Threshold concept theory and threshold capability theory provide a framework describing the features of the most critical and challenging learning in any discipline. The framework describes the effort of overcoming thresholds as troublesome, with a process that is often messy and long. Five coursework master's students, six postgraduate research students, and five academics were interviewed about their experiences with threshold concepts in signal processing. Two major threshold concepts were identified: time-frequency transformation and discretization. Self-regulated learning through years was needed to overcome the thresholds. Based on students' comments, the following are recommended to support learning in signal processing: integrated units, an introduction to how signals can be represented and why signal processing is used, examples of real applications, visualizations, practical laboratory exercises with prework, small applied projects throughout units, ample sample problems, the development of learning communities through consistent class groups, and opportunities to ask questions. Coursework and research students reported developing efficacy in self-directed learning as a consequence of overcoming threshold learning in signal processing.

Signal processing is an engineering discipline known to involve abstract and complex concepts. Curriculum development should be informed by an understanding of the most critical and challenging learning in the field. Threshold concept theory and threshold capability theory provide a framework describing the features of the most critical and challenging learning in any discipline. The framework describes the effort of overcoming thresholds as troublesome, with a process that is often messy and long. Five coursework master’s students, six postgraduate research students, and five academics were interviewed about their experiences with threshold concepts in signal processing. Two major threshold concepts were identified: time–frequency transformation and discretization. Self-regulated learning through years was needed to overcome the thresholds. Based on students’ comments, the following are recommended to support learning in signal processing: integrated units, an introduction to how signals can be represented and why signal processing is used, examples of real applications, visualizations, practical laboratory exercises with prework, small applied projects throughout units, ample sample problems, the development of learning communities through consistent class groups, and opportunities to ask questions. Coursework and research students reported developing efficacy in self-directed learning as a consequence of overcoming threshold learning in signal processing.

SPS on Twitter

  • RT : Call for Short Course proposals! in collaboration with the Education Board is planning education… https://t.co/N97XTEgIg8
  • This Wednesday, join the Information Forensics and Security Technical Committee Webinar Series when Dr. Richard Heu… https://t.co/ORdtuq5SlQ
  • Our Biomedical Imaging and Signal Processing Webinar Series continues on Tuesday, 5 July when Michael Unser present… https://t.co/7bYh8ZPHI0
  • Join us TODAY at 11:00 AM ET when the Brain Space Initiative Talk Series continues with Dr. Tianming Liu presenting… https://t.co/MEfnzk6dAE
  • Our 75th anniversary is approaching in 2023, and we're celebrating with a Special Issue of IEEE Signal Processing M… https://t.co/U6UNv8kLSO

SPS Videos


Signal Processing in Home Assistants

 


Multimedia Forensics


Careers in Signal Processing             

 


Under the Radar