Personalized learning plans for pre-requisite materials in a senior-level traffic engineering course

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Abstract

The purpose of this project was to improve a senior-level elective course on Traffic Operations at the Pennsylvania State University. Previous experiences with the course suggested that students generally have very poor recollection of various topics in statistics, which are required to appropriately analyze field data. Because of these deficiencies in prerequisite material, a significant portion of the course (about 4-5 of 30 lecture sessions) was spent reviewing background material. Doing so reduced the time available to spend on new material related to the course topic, broke momentum during the semester, and tended to be disengaging for students who did have sufficient background knowledge. Through a project with the Leonhard Center for Enhancement of Engineering Education within the College of Engineering, data-driven methods were developed to assess student competencies on this background material and provide personalized instructional modules to address any deficiencies. A pre-test on the prerequisite statistics material was created based on six unique topics that were deemed important to the course material. Students were asked to take the pretest during the first week of the course and their responses were used to provide them with targeted outside-of-the-classroom learning modules based on the specific material that they struggled with. Specifically, each question was associated with a unique module and a student only had to complete a module if they missed the associated question. These modules were comprised of reading assignments, YouTube videos and additional practice problems. Students were asked to turn in the additional problems for class credit. However, the problems themselves were not graded but were used to ensure students completed the necessary activities. During the fourth week, students were then asked to take a post-test to assess their knowledge of the prerequisite material, as well as their improvement on the topics that were most challenging. The results suggested that the targeted modules helped improve performance on the prerequisite material by about 40% on average and that student confidence in their abilities increased by about 45%. Moreover, moving the prerequisite material outside of the classroom helped free up additional time to cover topics related to the course material that could not be accommodated before, including signal coordination and actuated signal control. In general, this strategy appears to be effective and can be applied to any course to help address issues with prerequisite knowledge. This study is limited due to the relatively low sample size (total of 81 students), lack of a comparison group to compare traditional methods of teaching prerequisite material, and potential confounding factors that might have influenced results. However, the large improvements in performance and short-time frame that this was implemented in may help limit some of these impacts.

Original languageEnglish (US)
Article number1095
JournalASEE Annual Conference and Exposition, Conference Proceedings
Volume2020-June
StatePublished - Jun 22 2020
Event2020 ASEE Virtual Annual Conference, ASEE 2020 - Virtual, Online
Duration: Jun 22 2020Jun 26 2020

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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