Khalid, M; Yusuf, A; Akanmu, A; Murzi, H and Awolusi, I (2024) The impact of individual differences in developing computational thinking and sensor data analytics skills in construction engineering education. International Journal of Construction Education and Research, 20(4), pp. 483-500. ISSN 1557-8771
Abstract
The construction industry is a hazardous environment with a high prevalence of work-related musculoskeletal disorders, compromising workers’ physical and emotional well-being. Construction practitioners can leverage sensor-based safety assessment systems to track and identify workers’ awkward postures, preventing potential injuries. Educational sensor data practices with block programming can enable higher-order learning of the required computational skills for sensor data analytics. However, limited research exists on the factors influencing the acquisition of these skills in training graduating construction students. Through a sensor-based risk assessment intervention, this study explores how individual characteristics (demographics) influence students’ learning. Assessments included perceived self-efficacy of data analytics skills, analytical performance scores, and user acceptance of the educational platform. The results suggest: (a) women show higher self-efficacy gains, while Hispanic/Latino students and those without construction or programming experience report lesser gains, (b) students reach similar performance levels, but those with construction experience excel in reflection reports, and (c) students without construction experience perceive higher utility and lower risks, while Hispanic/Latino students show greater future intent to use the pedagogical tool. The findings contribute to Aptitude-Treatment Interaction Theory by highlighting how individual differences can impact the efficacy of pedagogical interventions in acquiring technical skills in construction education.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | block-based programming interface; computational thinking; construction education; sensor data analytics; workforce development |
| Index terms: | construction practitioner, injury, technical skill, sensor data, programming, workforce development, well-being, construction education, acquisition, platform, demographics, construction industry, interaction, self-efficacy, women, construction engineering, reflection, risk assessment |
| Subjects: | financial risk, digital design, professional development, engineering methods, industry analysis, behavioral psychology, demography, sociology, health conditions and diseases, professional education, programming, human factors and perception, mental health and wellbeing, business, research products and data |
| Topics: | Information Management, Engineering Principles, Research Practice, Health and Safety, Cost Management, Business Strategy, Education, Urban Studies, Digital Applications |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here