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Constructing and Visualizing Models using Mime-based Machine-learning Framework

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MEttLE: a modelling-based learning environment for undergraduate engineering estimation problem solving.

Aditi Kothiyal¹, Sahana Murthy¹

¹Interdisciplinary Program in Educational Technology, Indian Institute of Technology Bombay, Mumbai, India.

Research and Practice in Technology Enhanced Learning

|January 1, 2019

Summary

This summary is machine-generated.

This study introduces a technology-enhanced learning environment (TELE) to improve engineering students' estimation skills. The TELE successfully helped students solve estimation problems and understand the reasoning processes involved.

Keywords:

Design-based research Estimation Modelling Technology-enhanced learning environment

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Area of Science:

Engineering Education
Cognitive Science

Background:

Estimation is a critical skill for engineering undergraduates, yet it is often underemphasized in curricula.
Developing effective pedagogical approaches for teaching estimation is essential for engineering education.

Purpose of the Study:

To design and evaluate a technology-enhanced learning environment (TELE) for teaching engineering estimation.
To investigate the impact of TELE features on students' ability to perform estimation and understand the underlying reasoning processes.

Main Methods:

A design-based research approach was employed to develop the TELE.
A lab study was conducted to assess learners' use of the TELE and their performance on estimation tasks.
The TELE incorporates progressive, higher-order modeling, a problem system simulator, and metacognitive scaffolds.

Main Results:

Learners successfully utilized the TELE to solve estimation problems and achieve order-of-magnitude estimates.
Students demonstrated learning of estimation reasoning processes, including evaluation and practical considerations.
Specific TELE features were identified as crucial for facilitating the learning of these reasoning processes.

Conclusions:

The developed TELE is effective in supporting engineering students' learning of estimation.
The findings provide insights for refining the TELE to further enhance student learning of estimation skills.
Integrating technology and metacognitive support can address the underemphasis of estimation in engineering education.