Journal of Engineering Education Transformations

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Effect of Computer Learning on Performance in Early Architecture Education


Affiliations
1 School of Architecture, Christ University, Bangalore, India
2 Department of Architecture & Regional Planning, Indian Institute of Technology Kharagpur, West Bengal, India
     

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A mixed cohort of students with different experience backgrounds join the architecture degree. While some are well familiar with the user interface of computer and 3-D digital tools, others are not. The effect of such prior knowledge and their corresponding digital and analog performance in a designed experiment was evaluated with a sample of 38 first-year students. This was done to understand the performance effects of previous computer learning in students. Computer learning of the sample was studied in terms of years of computer exposure, the number of software known, and knowledge of 3D software or SketchUp. The results suggest that none of the factors contributed to the digital performance of students. This provided suggestions regarding the computer teaching emphasis which should be placed on students having less computer learning.

Keywords

Architecture Education, Sketching, Digital Tools, Digital Performance, Intuitive Interface, Mental Imagery.
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  • Baghaei Daemei, A., & Safari, H. (2018). Factors affecting creativity in the architectural education process based on computer-aided design. Frontiers of Architectural Research, 7(1), 100–106. https://doi.org/10.1016/j.foar.2017.09.001

  • Eastman, C., & Computing, D. (2001). New Directions in Design Cognition. Design Knowing and Learning: Cognition in Design Education, 147–198. doi:10.1016/b978-008043868-9/50008-5

  • Goldschmidt, G. (1994). On visual design thinking: The vis kids of architecture. Design Studies, 15(2), 158–174. https://doi.org/10.1016/0142-694X(94)90022-1

  • Goldschmidt, G. (1995) Visual displays for design: Imagery, analogy and databases of visual images, Ch-4, Visual databases in architecture: Recent advances in design and decision-making, Avebury. 53-74

  • Kavakli, M., Suwa, M., Gero, J., & Purcell, T. (1999). Sketching interpretation in novice and expert designers. (eds), Visual and Spatial Reasoning in Design, Key Centre of Design Computing and Cognition, University of Sydney, Sydney, Australia, pp. 209-220.

  • Kosslyn, S. M. (2005). Mental images and the brain. Cognitive Neuropsychology, 22(3/4), 333–347.

  • Lee, J., Ahn, J., Kim, J., Kho, J. M., & Paik, H. Y. (2018). Cognitive evaluation for conceptual design: Cognitive role of a 3D sculpture tool in the design thinking process. Digital Creativity, 29(4), 299–314. https://doi.org/10.1080/14626268.2018.1528988

  • Norman, D. A. (2013). The design of everyday things. MIT Press.

  • Pearson, J., Clifford, C. W. G., & Tong, F. (2008). The Functional Impact of Mental Imagery on Conscious Perception. Current Biology, 18(13), 982–986. https://doi.org/10.1016/j.cub.2008.05.048

  • Schön, D. A., & Wiggins, G. (1992). Kinds of Seeing in Designing. Creativity and Innovation Management, 1(2), 68–74. https://doi.org/10.1111/j.1467-8691.1992.tb00031.x

  • Zhang J. Patel V. L. (2006) Distributed cognition, representation, and affordance. Pragmatics & Cognition, 14(2), 333–341. https://doi.org/10.1075/pc.14.2.12zha


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  • Effect of Computer Learning on Performance in Early Architecture Education

Abstract Views: 244  |  PDF Views: 1

Authors

Vriddhi
School of Architecture, Christ University, Bangalore, India
Joy Sen
Department of Architecture & Regional Planning, Indian Institute of Technology Kharagpur, West Bengal, India

Abstract


A mixed cohort of students with different experience backgrounds join the architecture degree. While some are well familiar with the user interface of computer and 3-D digital tools, others are not. The effect of such prior knowledge and their corresponding digital and analog performance in a designed experiment was evaluated with a sample of 38 first-year students. This was done to understand the performance effects of previous computer learning in students. Computer learning of the sample was studied in terms of years of computer exposure, the number of software known, and knowledge of 3D software or SketchUp. The results suggest that none of the factors contributed to the digital performance of students. This provided suggestions regarding the computer teaching emphasis which should be placed on students having less computer learning.

Keywords


Architecture Education, Sketching, Digital Tools, Digital Performance, Intuitive Interface, Mental Imagery.

References





DOI: https://doi.org/10.16920/jeet%2F2022%2Fv35i4%2F22103