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Kaur, Rashpinder
- Case Study: Student's Response Towards Online Learning in Engineering Education During COVID-19 Pandemic
Abstract Views :292 |
PDF Views:117
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Punjab, IN
1 Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Punjab, IN
Source
Journal of Engineering Education Transformations, Vol 34, No 3 (2021), Pagination: 62-69Abstract
Novel Corona virus Disease (COVID-19) originated from Wuhan, China is widespread across the world so World Health Organization has declared COVID-19 as pandemic. As there is no vaccine available and this disease is transmitted though air so social distancing is one of the widely adopted strategy to control the spread of the COVID-19 pandemic. The education process all over the country was suspended due to announcement of National Lockdown in April, 2020 by the government of India. The Teaching Organizations and Management of Engineering Colleges and Universities in India during this Lockdown Period took initiative to continue education and teaching with Information Technology. This study attempted to investigate the quality of engineering education through online platforms in terms of knowledge gain, concept clarity, assessment, satisfaction level of students during the COVID-19 pandemic. An online survey was conducted and 123 student's responses were received. The student's response towards the online learning leads to conclusion that although the use of technologies in education is increased a lot but still learning through online mode will remain as supplementary material for the students. It cannot replace the traditional classroom teaching.Keywords
Online Learning, Pandemic, Technology.References
- Ansari, M. S., & Tripathi, A. (2017). An investigation of effectiveness of mobile learning apps in higher education in India. International Journal of Information Studies and Libraries, 2(1), 33–41.
- Kumar, A., Mantri, A., & Dutta, R. (2020). Development of an augmented reality-based scaffold to improve the learning experience of engineering students in embedded system course. Computer Applications in Engineering Education, October 2019, 1–14. https://doi.org/10.1002/cae.22245
- Majumder, A. J., & Sarma, G. K. (2010). Open Courseware initiatives for e-learners in India. http://arizona.openrepository.com/arizona/handle/10150/224211
- Peg u , U. K. (2014). Information and communication technology in higher education in India: Challenges and opportunities. International Journal of Information and Computation Technology, 4(5), 513–518. http://www.irphouse.com/ijict.htm
- Raman, R., Nedungadi, P., Achuthan, K., & Diwakar, S. (2011). Integrating Collaboration and Accessibility for Deploying Virtual Labs using VLCAP. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 2(5), 547–560.
- Roy, D., Tripathy, S., Kar, S. K., Sharma, N., Verma, S. K., & Kaushal, V. (2020). Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asi an Journal of Psychiatry, 51(April), 102083. https://doi.org/10.1016/j.ajp.2020.102083
- Shenoy, V., Mahendra, S., & Vijay, N. (2020). COVID 19 Lockdown Technology Adaption, Faculty Experience. Mukt Shabd Journal, 9(4), 698–702. https://www.res earchgat e.net/publication/340609688
- Singh, G., Mantri, A., Sharma, O., Dutta, R., & Kaur, R. (2019). Evaluating the impact of the augmented reality learning environment on electronics laboratory skills of engineering students. Computer Applications in Engineering Education, 27(6), 1361–1375. https://doi.org/10.1002/cae.22156
- Technology, C. (2012). Adoption of Web 2.0 technology in higher education: A case study of universities in National Capital Region, India Sunil Tyagi Ministry of Health & Family Welfare, Government of India. International Journal of Education and Development Using Information and Communication Technology, 8(2), 28–43.
- Using Concept Inventory for Assessing Conceptual Knowledge in the Signals and Systems Course
Abstract Views :39 |
PDF Views:2
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IN
2 Department of Psychology, St. Mary MacKillop College, ACT, AU
1 Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IN
2 Department of Psychology, St. Mary MacKillop College, ACT, AU
Source
Journal of Engineering Education Transformations, Vol 37, No 1 (2023), Pagination: 41-50Abstract
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 educationReferences
- 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