Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students

Daniel Manesh; Andy Luu; Mohammad Khalid; Jiangyue Li; Chinedu Okonkwo; Abiola Akanmu; Ibukun Awolusi; Homero Murzi; Sang Won Lee

doi:10.1109/VL-HCC57772.2023.00014

Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students

Daniel Manesh
, Andy Luu
, Mohammad Khalid
, Jiangyue Li
, Chinedu Okonkwo
, Abiola Akanmu
, Ibukun Awolusi
, Homero Murzi
, Sang Won Lee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

The construction industry is a new avenue for big data and data science with sensors and cyber-physical systems deployed in the field. Construction students need to develop computational thinking skills to help make sense of this data, but existing data science environments designed with textual programming languages create a significant barrier to entry. To bridge this gap, we introduce Octave, an end-user programming environment designed to help non-expert programmers analyze spatiotemporal data (e.g., as gathered by a GPS sensor) in an interactive graphical user interface. To aid exploration and understanding, Octave's design incorporates a high degree of liveness, highlighting the interconnection between data, computation, and visualization. We share the underlying design principles behind Octave and details about the system design and implementation. To evaluate Octave, we conducted a usability study with students studying construction. The results show that non-programmer construction students were able to learn Octave easily and were able to effectively use it to solve domain-specific problems from construction education. The participants appreciated Octave's liveness and felt they could easily connect it to real-life problems in their field. Our work informs the design of future accessible end-user programming environments for data analysis targeting non-experts.

Original language	English (US)
Title of host publication	Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023
Publisher	IEEE Computer Society
Pages	51-59
Number of pages	9
ISBN (Electronic)	9798350329469
DOIs	https://doi.org/10.1109/VL-HCC57772.2023.00014
State	Published - 2023
Externally published	Yes
Event	2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023 - Washington, United States Duration: Oct 2 2023 → Oct 6 2023

Publication series

Name	Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC
ISSN (Print)	1943-6092
ISSN (Electronic)	1943-6106

Conference

Conference	2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023
Country/Territory	United States
City	Washington
Period	10/2/23 → 10/6/23

All Science Journal Classification (ASJC) codes

Computational Theory and Mathematics
Human-Computer Interaction
Software

Keywords

Construction
Data analytics
End-user Programming
Spatiotemporal Data
Spreadsheets

Access to Document

10.1109/VL-HCC57772.2023.00014

Cite this

Manesh, D., Luu, A., Khalid, M., Li, J., Okonkwo, C., Akanmu, A., Awolusi, I., Murzi, H., & Lee, S. W. (2023). Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students. In Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023 (pp. 51-59). (Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC). IEEE Computer Society. https://doi.org/10.1109/VL-HCC57772.2023.00014

Manesh, Daniel ; Luu, Andy ; Khalid, Mohammad et al. / Octave : An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students. Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023. IEEE Computer Society, 2023. pp. 51-59 (Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC).

@inproceedings{2ff2df4c5e0f407c8678d1213e08d9fc,

title = "Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students",

abstract = "The construction industry is a new avenue for big data and data science with sensors and cyber-physical systems deployed in the field. Construction students need to develop computational thinking skills to help make sense of this data, but existing data science environments designed with textual programming languages create a significant barrier to entry. To bridge this gap, we introduce Octave, an end-user programming environment designed to help non-expert programmers analyze spatiotemporal data (e.g., as gathered by a GPS sensor) in an interactive graphical user interface. To aid exploration and understanding, Octave's design incorporates a high degree of liveness, highlighting the interconnection between data, computation, and visualization. We share the underlying design principles behind Octave and details about the system design and implementation. To evaluate Octave, we conducted a usability study with students studying construction. The results show that non-programmer construction students were able to learn Octave easily and were able to effectively use it to solve domain-specific problems from construction education. The participants appreciated Octave's liveness and felt they could easily connect it to real-life problems in their field. Our work informs the design of future accessible end-user programming environments for data analysis targeting non-experts.",

keywords = "Construction, Data analytics, End-user Programming, Spatiotemporal Data, Spreadsheets",

author = "Daniel Manesh and Andy Luu and Mohammad Khalid and Jiangyue Li and Chinedu Okonkwo and Abiola Akanmu and Ibukun Awolusi and Homero Murzi and Lee, \{Sang Won\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023 ; Conference date: 02-10-2023 Through 06-10-2023",

year = "2023",

doi = "10.1109/VL-HCC57772.2023.00014",

language = "English (US)",

series = "Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC",

publisher = "IEEE Computer Society",

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booktitle = "Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023",

address = "United States",

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Manesh, D, Luu, A, Khalid, M, Li, J, Okonkwo, C, Akanmu, A, Awolusi, I, Murzi, H & Lee, SW 2023, Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students. in Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023. Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, IEEE Computer Society, pp. 51-59, 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023, Washington, United States, 10/2/23. https://doi.org/10.1109/VL-HCC57772.2023.00014

Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students. / Manesh, Daniel; Luu, Andy; Khalid, Mohammad et al.
Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023. IEEE Computer Society, 2023. p. 51-59 (Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Octave

T2 - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023

AU - Manesh, Daniel

AU - Luu, Andy

AU - Khalid, Mohammad

AU - Li, Jiangyue

AU - Okonkwo, Chinedu

AU - Akanmu, Abiola

AU - Awolusi, Ibukun

AU - Murzi, Homero

AU - Lee, Sang Won

PY - 2023

Y1 - 2023

N2 - The construction industry is a new avenue for big data and data science with sensors and cyber-physical systems deployed in the field. Construction students need to develop computational thinking skills to help make sense of this data, but existing data science environments designed with textual programming languages create a significant barrier to entry. To bridge this gap, we introduce Octave, an end-user programming environment designed to help non-expert programmers analyze spatiotemporal data (e.g., as gathered by a GPS sensor) in an interactive graphical user interface. To aid exploration and understanding, Octave's design incorporates a high degree of liveness, highlighting the interconnection between data, computation, and visualization. We share the underlying design principles behind Octave and details about the system design and implementation. To evaluate Octave, we conducted a usability study with students studying construction. The results show that non-programmer construction students were able to learn Octave easily and were able to effectively use it to solve domain-specific problems from construction education. The participants appreciated Octave's liveness and felt they could easily connect it to real-life problems in their field. Our work informs the design of future accessible end-user programming environments for data analysis targeting non-experts.

AB - The construction industry is a new avenue for big data and data science with sensors and cyber-physical systems deployed in the field. Construction students need to develop computational thinking skills to help make sense of this data, but existing data science environments designed with textual programming languages create a significant barrier to entry. To bridge this gap, we introduce Octave, an end-user programming environment designed to help non-expert programmers analyze spatiotemporal data (e.g., as gathered by a GPS sensor) in an interactive graphical user interface. To aid exploration and understanding, Octave's design incorporates a high degree of liveness, highlighting the interconnection between data, computation, and visualization. We share the underlying design principles behind Octave and details about the system design and implementation. To evaluate Octave, we conducted a usability study with students studying construction. The results show that non-programmer construction students were able to learn Octave easily and were able to effectively use it to solve domain-specific problems from construction education. The participants appreciated Octave's liveness and felt they could easily connect it to real-life problems in their field. Our work informs the design of future accessible end-user programming environments for data analysis targeting non-experts.

KW - Construction

KW - Data analytics

KW - End-user Programming

KW - Spatiotemporal Data

KW - Spreadsheets

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UR - https://www.scopus.com/pages/publications/85178640182#tab=citedBy

U2 - 10.1109/VL-HCC57772.2023.00014

DO - 10.1109/VL-HCC57772.2023.00014

M3 - Conference contribution

AN - SCOPUS:85178640182

T3 - Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC

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BT - Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023

PB - IEEE Computer Society

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Manesh D, Luu A, Khalid M, Li J, Okonkwo C, Akanmu A et al. Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students. In Proceedings - 2023 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2023. IEEE Computer Society. 2023. p. 51-59. (Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC). doi: 10.1109/VL-HCC57772.2023.00014

Octave: An End-User Programming Environment for Analysis of Spatiotemporal Data for Construction Students

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

Keywords

Access to Document

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