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Although there is extensive literature documenting hands-on learning experiences in engineering classrooms, there is a lack of consensus regarding how student learning during these activities compares to learning during online video demonstrations. Further, little work has been done to directly compare student learning for similarly-designed hands-on learning experiences focused on different engineering subjects. As the use of hands-on activities in engineering continues to grow and expand to non-traditional virtual applications, understanding how to optimize student learning during these activities is critical. To address this, we collected conceptual assessment data from 763 students at 15 four-year institutions. The students completed activities with one of two highly visual low-cost desktop learning modules (LCDLMs), one focused on fluid mechanics and the other on heat transfer principles, using two different implementation formats: either hands-on or video demonstration. To examine the effect of implementation format and of the learning tool used, learning gains on conceptual assessments were compared for virtual and hands-on implementations of fluid mechanics and heat transfer LCDLMs. Results showed that learning gains were positive and similar for hands-on and video demonstrations for both modules assessed, suggesting both implementation formats support an impactful student learning experience. However, a significant difference was observed in effectiveness based on the type of LCDLM used. Score increases of 31.2% and 24% were recorded on our post-activity assessment for hands-on and virtual implementations of the fluid mechanics LCDLM compared to pre-activity assessment scores, respectively, while smaller 8.2% and 9.2% increases were observed for hands-on and virtual implementations of the heat transfer LCDLM. In this paper, we consider existing literature to ascertain the reasons for similar effectiveness of hands-on and video demonstrations and for the differing effectiveness of the fluid mechanics and heat transfer LCDLMs. We discuss the practical implications of our findings with respect to designing hands-on or video demonstration activities.
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Anonymized Two-Way Traffic Packet Header Traces (2025)
This dataset contains anonymized layer 1-4 packet headers of two-way passive traces captured on a 100 GB link between Los Angeles and Dallas. These data are useful for research on the characteristics of Internet traffic, including application breakdown, security events, geographic and topological distribution, flow volume and duration.
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- PAR ID:
- 10616742
- Publisher / Repository:
- CAIDA UCSD
- Date Published:
- Subject(s) / Keyword(s):
- Internet two-way traffic Anonymized Internet traces Passive Internet measurement 100 GB link
- Format(s):
- Medium: X Size: 2TB Other: pcap
- Size(s):
- 2TB
- Right(s):
- CAIDA UCSD; The Regents of the University of California
- Institution:
- CAIDA
- Sponsoring Org:
- National Science Foundation
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