Journal of Engineering Education Transformations

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Using Concept Inventory for Assessing Conceptual Knowledge in the Signals and Systems Course


Affiliations
1 Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
2 Department of Psychology, St. Mary MacKillop College, ACT, Australia
     

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The engineering schools usually target problem-solving skills in students instead of conceptual development, which is an essential skill for transformation from novice to professional engineer as per the program objective. Improving a student's conceptual knowledge can help students understand a problem better and develop a better solution. Conceptual understanding also assists students in identifying gaps in their problem-solving techniques. This paper attempts to administer a Signal and System Concept Inventory (SSCI) to test the conceptual knowledge of core concepts of signals and systems course and then identify the correlation of post-test scores with the student's performance in the end-term exam. The result shows that the students who scored above 80% in concept inventory also performed outstanding in the end-term examination. The result also indicates that most of the students able solve questions on background mathematics and pole- zero plots but struggled with convolution and Fourier analysis.

Keywords

concept inventory, conceptual understanding, assessment, engineering education
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  • Boles, W., Goncher, A., & Jayalath, D. (2015). Uncovering misconceptions through text analysis. 6th Research in Engineering Education Symposium: Translating Research into Practice, REES 2015, July, 13–15.

  • Fayyaz, F. (2014). A qualitative study of problematic reasoning’s of undergraduate electrical engineering students in Continuous Time Signals and Systems courses. http://docs.lib.purdue.edu/open_access_disserta tions.

  • Padgett, W. T., Yoder, M. A., & Forbes, S. A. (2011). Extending the usefulness of the Signals and Systems Concept Inventory (SSCI). 2011 Digital Signal Processing and Signal Processing Education Meeting, DSP/ SPE 2011 Proceedings, 204-209. https://doi.org/10.1109/DSP-SPE.2011.5739212

  • Rahmawati, Rustaman, N. Y., Hamidah, I., & Rusdiana, D. (2018). The development and validation of conceptual knowledge test to evaluate conceptual knowledge of physics prospective teachers on electricity and magnetism topic. Jurnal Pendidikan IPA Indonesia, 7(4), 483-490. https://doi.org/10.15294/jpii.v7i4.13490

  • Sands, D., Parker, M., Hedgeland, H., Jordan, S., & Galloway, R. (2018). Using concept inventories to measure understanding. Higher Education Pedagogies, 3 (1 ) , 173 – 182 . https://doi.org/10.1080/23752696.2018.143354 6

  • Streveler, R. A., Litzinger, T. A., Miller, R. L., & Steif, P. S. (2008). Learning conceptual knowledge in the engineering sciences: Overview and future research directions. Journal of Engineering Education, 97(3), 279–294. https://doi.org/10.1002/j.2168-9830.2008.tb00979.x

  • Taraban, R., Anderson, E. E., DeFinis, A., Brown, A. G., Weigold, A., & Sharma, M. P. (2007). First steps in understanding engineering students growth of conceptual and procedural knowledge in an interactive learning context. Journal of Engineering Education, 96(1), 57–68. https://doi.org/10.1002/j.2168-9830.2007.tb00915.x

  • Taraban, R., DeFinis, A., Brown, A. G., Anderson, E. E., & Sharma, M. P. (2007). A paradigm for assessing conceptual and procedural knowledge in engineering students. Journal of Engineering Education, 96(4), 335–345. https://doi.org/10.1002/j.2168- 9830.2007.tb00943.x

  • Wage, K. E., Buck, J. R., Welch, T. B., & Wright, C. H. G. (2002). Testing and validation of the signals and systems concept inventory. Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, DSP 2002 and 2nd Signal Processing Education Workshop, SPE 2002, 151-156. https://doi.org/10.1109/DSPWS.2002.1231094

  • Wage, Kathleen E., Buck, J. R., & Hjalmarson, M. A. (2006). Analyzing misconceptions using the signals and systems concept inventory and student interviews. 2006 IEEE 12th Digital Signal Processing Workshop and 4th IEEE Signal Processing Education Workshop, 123–128. https://doi.org/10.1109/DSPWS.2006.265451

  • Wage, Kathleen E., Buck, J. R., Hjalmarson, M. A., & Nelson, J. K. (2011). Signals and systems assessment: Comparison of responses to multiple choice conceptual questions and open-ended final exam problems. 2011 Digital Signal Processing and Signal Processing Education Meeting, DSP/SPE 2011 - Proceedings, 198 – 203. https:// doi. org/ 10 . 1109 / DSP- SPE.2011.5739211

  • Wage, Kathleen E., Buck, J. R., Wright, C. C. H. G., & Welch, T. B. (2005). The signals and systems concept inventory. IEEE Transactions on Education, 48(3), 448–461. https://doi.org/10.1109/TE.2005.849746v


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  • Using Concept Inventory for Assessing Conceptual Knowledge in the Signals and Systems Course

Abstract Views: 153  |  PDF Views: 2

Authors

Rashpinder Kaur
Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
Archana Mantri
Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India
Prathiba Nagabhushan
Department of Psychology, St. Mary MacKillop College, ACT, Australia
Gurjinder Singh
Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

Abstract


The engineering schools usually target problem-solving skills in students instead of conceptual development, which is an essential skill for transformation from novice to professional engineer as per the program objective. Improving a student's conceptual knowledge can help students understand a problem better and develop a better solution. Conceptual understanding also assists students in identifying gaps in their problem-solving techniques. This paper attempts to administer a Signal and System Concept Inventory (SSCI) to test the conceptual knowledge of core concepts of signals and systems course and then identify the correlation of post-test scores with the student's performance in the end-term exam. The result shows that the students who scored above 80% in concept inventory also performed outstanding in the end-term examination. The result also indicates that most of the students able solve questions on background mathematics and pole- zero plots but struggled with convolution and Fourier analysis.

Keywords


concept inventory, conceptual understanding, assessment, engineering education

References